TY - THES A1 - Hesse, Günter T1 - A benchmark for enterprise stream processing architectures T1 - Ein Benchmark für Architekturen zur Datenstromverarbeitung im Unternehmenskontext N2 - Data stream processing systems (DSPSs) are a key enabler to integrate continuously generated data, such as sensor measurements, into enterprise applications. DSPSs allow to steadily analyze information from data streams, e.g., to monitor manufacturing processes and enable fast reactions to anomalous behavior. Moreover, DSPSs continuously filter, sample, and aggregate incoming streams of data, which reduces the data size, and thus data storage costs. The growing volumes of generated data have increased the demand for high-performance DSPSs, leading to a higher interest in these systems and to the development of new DSPSs. While having more DSPSs is favorable for users as it allows choosing the system that satisfies their requirements the most, it also introduces the challenge of identifying the most suitable DSPS regarding current needs as well as future demands. Having a solution to this challenge is important because replacements of DSPSs require the costly re-writing of applications if no abstraction layer is used for application development. However, quantifying performance differences between DSPSs is a difficult task. Existing benchmarks fail to integrate all core functionalities of DSPSs and lack tool support, which hinders objective result comparisons. Moreover, no current benchmark covers the combination of streaming data with existing structured business data, which is particularly relevant for companies. This thesis proposes a performance benchmark for enterprise stream processing called ESPBench. With enterprise stream processing, we refer to the combination of streaming and structured business data. Our benchmark design represents real-world scenarios and allows for an objective result comparison as well as scaling of data. The defined benchmark query set covers all core functionalities of DSPSs. The benchmark toolkit automates the entire benchmark process and provides important features, such as query result validation and a configurable data ingestion rate. To validate ESPBench and to ease the use of the benchmark, we propose an example implementation of the ESPBench queries leveraging the Apache Beam software development kit (SDK). The Apache Beam SDK is an abstraction layer designed for developing stream processing applications that is applied in academia as well as enterprise contexts. It allows to run the defined applications on any of the supported DSPSs. The performance impact of Apache Beam is studied in this dissertation as well. The results show that there is a significant influence that differs among DSPSs and stream processing applications. For validating ESPBench, we use the example implementation of the ESPBench queries developed using the Apache Beam SDK. We benchmark the implemented queries executed on three modern DSPSs: Apache Flink, Apache Spark Streaming, and Hazelcast Jet. The results of the study prove the functioning of ESPBench and its toolkit. ESPBench is capable of quantifying performance characteristics of DSPSs and of unveiling differences among systems. The benchmark proposed in this thesis covers all requirements to be applied in enterprise stream processing settings, and thus represents an improvement over the current state-of-the-art. N2 - Data Stream Processing Systems (DSPSs) sind eine Schlüsseltechnologie, um kontinuierlich generierte Daten, wie beispielsweise Sensormessungen, in Unternehmensanwendungen zu integrieren. Die durch DSPSs ermöglichte permanente Analyse von Datenströmen kann dabei zur Überwachung von Produktionsprozessen genutzt werden, um möglichst zeitnah auf ungewollte Veränderungen zu reagieren. Darüber hinaus filtern, sampeln und aggregieren DSPSs einkommende Daten, was die Datengröße reduziert und so auch etwaige Kosten für die Datenspeicherung. Steigende Datenvolumen haben in den letzten Jahren den Bedarf für performante DSPSs steigen lassen, was zur Entwicklung neuer DSPSs führte. Während eine große Auswahl an verfügbaren Systemen generell gut für Nutzer ist, stellt es potentielle Anwender auch vor die Herausforderung, das für aktuelle und zukünftige Anforderungen passendste DSPS zu identifizieren. Es ist wichtig, eine Lösung für diese Herausforderung zu haben, da das Austauschen von einem DSPS zu teuren Anpassungen oder Neuentwicklungen der darauf laufenden Anwendungen erfordert, falls für deren Entwicklung keine Abstraktionsschicht verwendet wurde. Das quantitative Vergleichen von DSPSs ist allerdings eine schwierige Aufgabe. Existierende Benchmarks decken nicht alle Kernfunktionalitäten von DSPSs ab und haben keinen oder unzureichenden Tool-Support, was eine objektive Ergebnisberechnung hinsichtlich der Performanz erschwert. Zudem beinhaltet kein Benchmark die Integration von Streamingdaten und strukturierten Geschäftsdaten, was ein besonders für Unternehmen relevantes Szenario ist. Diese Dissertation stellt ESPBench vor, einen neuen Benchmark für Stream Processing-Szenarien im Unternehmenskontext. Der geschäftliche Kontext wird dabei durch die Verbindung von Streamingdaten und Geschäftsdaten dargestellt. Das Design von ESPBench repräsentiert Szenarien der realen Welt, stellt die objektive Berechnung von Benchmarkergebnissen sicher und erlaubt das Skalieren über Datencharakteristiken. Das entwickelte Toolkit des Benchmarks stellt wichtige Funktionalitäten bereit, wie beispielsweise die Automatisierung den kompletten Benchmarkprozesses sowie die Überprüfung der Abfrageergebnisse hinsichtlich ihrer Korrektheit. Um ESPBench zu validieren und die Anwendung weiter zu vereinfachen, haben wir eine Beispielimplementierung der Queries veröffentlicht. Die Implementierung haben wir mithilfe des in Industrie und Wissenschaft eingesetzten Softwareentwicklungsbaukastens Apache Beam durchgeführt, der es ermöglicht, entwickelte Anwendungen auf allen unterstützten DSPSs auszuführen. Den Einfluss auf die Performanz des Verwendens von Apache Beam wird dabei ebenfalls in dieser Arbeit untersucht. Weiterhin nutzen wir die veröffentlichte Beispielimplementierung der Queries um drei moderne DSPSs mit ESPBench zu untersuchen: Apache Flink, Apache Spark Streaming und Hazelcast Jet. Der Ergebnisse der Studie verdeutlichen die Funktionsfähigkeit von ESPBench und dessen Toolkit. ESPBench befähigt Performanzcharakteristiken von DSPSs zu quantifizieren und Unterschiede zwischen Systemen aufzuzeigen. Der in dieser Dissertation vorgestellte Benchmark erfüllt alle Anforderungen, um in Stream Processing-Szenarien im Unternehmenskontext eingesetzt zu werden und stellt somit eine Verbesserung der aktuellen Situation dar. KW - stream processing KW - performance KW - benchmarking KW - dsps KW - espbench KW - benchmark KW - Performanz KW - Datenstromverarbeitung KW - Benchmark Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-566000 ER - TY - GEN A1 - Galke, Lukas A1 - Gerstenkorn, Gunnar A1 - Scherp, Ansgar T1 - A case atudy of closed-domain response suggestion with limited training data T2 - Database and Expert Systems Applications : DEXA 2018 Iinternational workshops N2 - We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation. Y1 - 2018 SN - 978-3-319-99133-7 SN - 978-3-319-99132-0 U6 - https://doi.org/10.1007/978-3-319-99133-7_18 SN - 1865-0929 SN - 1865-0937 VL - 903 SP - 218 EP - 229 PB - Springer CY - Berlin ER - TY - JOUR A1 - Wuttke, Matthias A1 - Li, Yong A1 - Li, Man A1 - Sieber, Karsten B. A1 - Feitosa, Mary F. A1 - Gorski, Mathias A1 - Tin, Adrienne A1 - Wang, Lihua A1 - Chu, Audrey Y. A1 - Hoppmann, Anselm A1 - Kirsten, Holger A1 - Giri, Ayush A1 - Chai, Jin-Fang A1 - Sveinbjornsson, Gardar A1 - Tayo, Bamidele O. A1 - Nutile, Teresa A1 - Fuchsberger, Christian A1 - Marten, Jonathan A1 - Cocca, Massimiliano A1 - Ghasemi, Sahar A1 - Xu, Yizhe A1 - Horn, Katrin A1 - Noce, Damia A1 - Van der Most, Peter J. A1 - Sedaghat, Sanaz A1 - Yu, Zhi A1 - Akiyama, Masato A1 - Afaq, Saima A1 - Ahluwalia, Tarunveer Singh A1 - Almgren, Peter A1 - Amin, Najaf A1 - Arnlov, Johan A1 - Bakker, Stephan J. L. A1 - Bansal, Nisha A1 - Baptista, Daniela A1 - Bergmann, Sven A1 - Biggs, Mary L. A1 - Biino, Ginevra A1 - Boehnke, Michael A1 - Boerwinkle, Eric A1 - Boissel, Mathilde A1 - Böttinger, Erwin A1 - Boutin, Thibaud S. A1 - Brenner, Hermann A1 - Brumat, Marco A1 - Burkhardt, Ralph A1 - Butterworth, Adam S. A1 - Campana, Eric A1 - Campbell, Archie A1 - Campbell, Harry A1 - Canouil, Mickael A1 - Carroll, Robert J. A1 - Catamo, Eulalia A1 - Chambers, John C. A1 - Chee, Miao-Ling A1 - Chee, Miao-Li A1 - Chen, Xu A1 - Cheng, Ching-Yu A1 - Cheng, Yurong A1 - Christensen, Kaare A1 - Cifkova, Renata A1 - Ciullo, Marina A1 - Concas, Maria Pina A1 - Cook, James P. A1 - Coresh, Josef A1 - Corre, Tanguy A1 - Sala, Cinzia Felicita A1 - Cusi, Daniele A1 - Danesh, John A1 - Daw, E. Warwick A1 - De Borst, Martin H. A1 - De Grandi, Alessandro A1 - De Mutsert, Renee A1 - De Vries, Aiko P. J. A1 - Degenhardt, Frauke A1 - Delgado, Graciela A1 - Demirkan, Ayse A1 - Di Angelantonio, Emanuele A1 - Dittrich, Katalin A1 - Divers, Jasmin A1 - Dorajoo, Rajkumar A1 - Eckardt, Kai-Uwe A1 - Ehret, Georg A1 - Elliott, Paul A1 - Endlich, Karlhans A1 - Evans, Michele K. A1 - Felix, Janine F. A1 - Foo, Valencia Hui Xian A1 - Franco, Oscar H. A1 - Franke, Andre A1 - Freedman, Barry I. A1 - Freitag-Wolf, Sandra A1 - Friedlander, Yechiel A1 - Froguel, Philippe A1 - Gansevoort, Ron T. A1 - Gao, He A1 - Gasparini, Paolo A1 - Gaziano, J. Michael A1 - Giedraitis, Vilmantas A1 - Gieger, Christian A1 - Girotto, Giorgia A1 - Giulianini, Franco A1 - Gogele, Martin A1 - Gordon, Scott D. A1 - Gudbjartsson, Daniel F. A1 - Gudnason, Vilmundur A1 - Haller, Toomas A1 - Hamet, Pavel A1 - Harris, Tamara B. A1 - Hartman, Catharina A. A1 - Hayward, Caroline A1 - Hellwege, Jacklyn N. A1 - Heng, Chew-Kiat A1 - Hicks, Andrew A. A1 - Hofer, Edith A1 - Huang, Wei A1 - Hutri-Kahonen, Nina A1 - Hwang, Shih-Jen A1 - Ikram, M. Arfan A1 - Indridason, Olafur S. A1 - Ingelsson, Erik A1 - Ising, Marcus A1 - Jaddoe, Vincent W. V. A1 - Jakobsdottir, Johanna A1 - Jonas, Jost B. A1 - Joshi, Peter K. A1 - Josyula, Navya Shilpa A1 - Jung, Bettina A1 - Kahonen, Mika A1 - Kamatani, Yoichiro A1 - Kammerer, Candace M. A1 - Kanai, Masahiro A1 - Kastarinen, Mika A1 - Kerr, Shona M. A1 - Khor, Chiea-Chuen A1 - Kiess, Wieland A1 - Kleber, Marcus E. A1 - Koenig, Wolfgang A1 - Kooner, Jaspal S. A1 - Korner, Antje A1 - Kovacs, Peter A1 - Kraja, Aldi T. A1 - Krajcoviechova, Alena A1 - Kramer, Holly A1 - Kramer, Bernhard K. A1 - Kronenberg, Florian A1 - Kubo, Michiaki A1 - Kuhnel, Brigitte A1 - Kuokkanen, Mikko A1 - Kuusisto, Johanna A1 - La Bianca, Martina A1 - Laakso, Markku A1 - Lange, Leslie A. A1 - Langefeld, Carl D. A1 - Lee, Jeannette Jen-Mai A1 - Lehne, Benjamin A1 - Lehtimaki, Terho A1 - Lieb, Wolfgang A1 - Lim, Su-Chi A1 - Lind, Lars A1 - Lindgren, Cecilia M. A1 - Liu, Jun A1 - Liu, Jianjun A1 - Loeffler, Markus A1 - Loos, Ruth J. F. A1 - Lucae, Susanne A1 - Lukas, Mary Ann A1 - Lyytikainen, Leo-Pekka A1 - Magi, Reedik A1 - Magnusson, Patrik K. E. A1 - Mahajan, Anubha A1 - Martin, Nicholas G. A1 - Martins, Jade A1 - Marz, Winfried A1 - Mascalzoni, Deborah A1 - Matsuda, Koichi A1 - Meisinger, Christa A1 - Meitinger, Thomas A1 - Melander, Olle A1 - Metspalu, Andres A1 - Mikaelsdottir, Evgenia K. A1 - Milaneschi, Yuri A1 - Miliku, Kozeta A1 - Mishra, Pashupati P. A1 - Program, V. A. Million Veteran A1 - Mohlke, Karen L. A1 - Mononen, Nina A1 - Montgomery, Grant W. A1 - Mook-Kanamori, Dennis O. A1 - Mychaleckyj, Josyf C. A1 - Nadkarni, Girish N. A1 - Nalls, Mike A. A1 - Nauck, Matthias A1 - Nikus, Kjell A1 - Ning, Boting A1 - Nolte, Ilja M. A1 - Noordam, Raymond A1 - Olafsson, Isleifur A1 - Oldehinkel, Albertine J. A1 - Orho-Melander, Marju A1 - Ouwehand, Willem H. A1 - Padmanabhan, Sandosh A1 - Palmer, Nicholette D. A1 - Palsson, Runolfur A1 - Penninx, Brenda W. J. H. A1 - Perls, Thomas A1 - Perola, Markus A1 - Pirastu, Mario A1 - Pirastu, Nicola A1 - Pistis, Giorgio A1 - Podgornaia, Anna I. A1 - Polasek, Ozren A1 - Ponte, Belen A1 - Porteous, David J. A1 - Poulain, Tanja A1 - Pramstaller, Peter P. A1 - Preuss, Michael H. A1 - Prins, Bram P. A1 - Province, Michael A. A1 - Rabelink, Ton J. A1 - Raffield, Laura M. A1 - Raitakari, Olli T. A1 - Reilly, Dermot F. A1 - Rettig, Rainer A1 - Rheinberger, Myriam A1 - Rice, Kenneth M. A1 - Ridker, Paul M. A1 - Rivadeneira, Fernando A1 - Rizzi, Federica A1 - Roberts, David J. A1 - Robino, Antonietta A1 - Rossing, Peter A1 - Rudan, Igor A1 - Rueedi, Rico A1 - Ruggiero, Daniela A1 - Ryan, Kathleen A. A1 - Saba, Yasaman A1 - Sabanayagam, Charumathi A1 - Salomaa, Veikko A1 - Salvi, Erika A1 - Saum, Kai-Uwe A1 - Schmidt, Helena A1 - Schmidt, Reinhold A1 - Ben Schottker, A1 - Schulz, Christina-Alexandra A1 - Schupf, Nicole A1 - Shaffer, Christian M. A1 - Shi, Yuan A1 - Smith, Albert V. A1 - Smith, Blair H. A1 - Soranzo, Nicole A1 - Spracklen, Cassandra N. A1 - Strauch, Konstantin A1 - Stringham, Heather M. A1 - Stumvoll, Michael A1 - Svensson, Per O. A1 - Szymczak, Silke A1 - Tai, E-Shyong A1 - Tajuddin, Salman M. A1 - Tan, Nicholas Y. Q. A1 - Taylor, Kent D. A1 - Teren, Andrej A1 - Tham, Yih-Chung A1 - Thiery, Joachim A1 - Thio, Chris H. L. A1 - Thomsen, Hauke A1 - Thorleifsson, Gudmar A1 - Toniolo, Daniela A1 - Tonjes, Anke A1 - Tremblay, Johanne A1 - Tzoulaki, Ioanna A1 - Uitterlinden, Andre G. A1 - Vaccargiu, Simona A1 - Van Dam, Rob M. A1 - Van der Harst, Pim A1 - Van Duijn, Cornelia M. A1 - Edward, Digna R. Velez A1 - Verweij, Niek A1 - Vogelezang, Suzanne A1 - Volker, Uwe A1 - Vollenweider, Peter A1 - Waeber, Gerard A1 - Waldenberger, Melanie A1 - Wallentin, Lars A1 - Wang, Ya Xing A1 - Wang, Chaolong A1 - Waterworth, Dawn M. A1 - Bin Wei, Wen A1 - White, Harvey A1 - Whitfield, John B. A1 - Wild, Sarah H. A1 - Wilson, James F. A1 - Wojczynski, Mary K. A1 - Wong, Charlene A1 - Wong, Tien-Yin A1 - Xu, Liang A1 - Yang, Qiong A1 - Yasuda, Masayuki A1 - Yerges-Armstrong, Laura M. A1 - Zhang, Weihua A1 - Zonderman, Alan B. A1 - Rotter, Jerome I. A1 - Bochud, Murielle A1 - Psaty, Bruce M. A1 - Vitart, Veronique A1 - Wilson, James G. A1 - Dehghan, Abbas A1 - Parsa, Afshin A1 - Chasman, Daniel I. A1 - Ho, Kevin A1 - Morris, Andrew P. A1 - Devuyst, Olivier A1 - Akilesh, Shreeram A1 - Pendergrass, Sarah A. A1 - Sim, Xueling A1 - Boger, Carsten A. A1 - Okada, Yukinori A1 - Edwards, Todd L. A1 - Snieder, Harold A1 - Stefansson, Kari A1 - Hung, Adriana M. A1 - Heid, Iris M. A1 - Scholz, Markus A1 - Teumer, Alexander A1 - Kottgen, Anna A1 - Pattaro, Cristian T1 - A catalog of genetic loci associated with kidney function from analyses of a million individuals JF - Nature genetics N2 - Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through transancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these,147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research. Y1 - 2019 U6 - https://doi.org/10.1038/s41588-019-0407-x SN - 1061-4036 SN - 1546-1718 VL - 51 IS - 6 SP - 957 EP - + PB - Nature Publ. Group CY - New York ER - TY - GEN A1 - Halfpap, Stefan A1 - Schlosser, Rainer T1 - A Comparison of Allocation Algorithms for Partially Replicated Databases T2 - 2019 IEEE 35th International Conference on Data Engineering (ICDE) N2 - Increasing demand for analytical processing capabilities can be managed by replication approaches. However, to evenly balance the replicas' workload shares while at the same time minimizing the data replication factor is a highly challenging allocation problem. As optimal solutions are only applicable for small problem instances, effective heuristics are indispensable. In this paper, we test and compare state-of-the-art allocation algorithms for partial replication. By visualizing and exploring their (heuristic) solutions for different benchmark workloads, we are able to derive structural insights and to detect an algorithm's strengths as well as its potential for improvement. Further, our application enables end-to-end evaluations of different allocations to verify their theoretical performance. Y1 - 2019 SN - 978-1-5386-7474-1 SN - 978-1-5386-7475-8 U6 - https://doi.org/10.1109/ICDE.2019.00226 SN - 1084-4627 SN - 2375-026X SN - 1063-6382 SP - 2008 EP - 2011 PB - IEEE CY - New York ER - TY - GEN A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Kayem, Anne V. D. M. A1 - Cheng, Feng A1 - Meinel, Christoph T1 - A cyber risk based moving target defense mechanism for microservice architectures T2 - IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications (ISPA/IUCC/BDCloud/SocialCom/SustainCom) N2 - Microservice Architectures (MSA) structure applications as a collection of loosely coupled services that implement business capabilities. The key advantages of MSA include inherent support for continuous deployment of large complex applications, agility and enhanced productivity. However, studies indicate that most MSA are homogeneous, and introduce shared vulnerabilites, thus vulnerable to multi-step attacks, which are economics-of-scale incentives to attackers. In this paper, we address the issue of shared vulnerabilities in microservices with a novel solution based on the concept of Moving Target Defenses (MTD). Our mechanism works by performing risk analysis against microservices to detect and prioritize vulnerabilities. Thereafter, security risk-oriented software diversification is employed, guided by a defined diversification index. The diversification is performed at runtime, leveraging both model and template based automatic code generation techniques to automatically transform programming languages and container images of the microservices. Consequently, the microservices attack surfaces are altered thereby introducing uncertainty for attackers while reducing the attackability of the microservices. Our experiments demonstrate the efficiency of our solution, with an average success rate of over 70% attack surface randomization. KW - Security Risk Assessment KW - Security Metrics KW - Moving Target Defense KW - Microservices Security KW - Application Container Security Y1 - 2018 SN - 978-1-7281-1141-4 U6 - https://doi.org/10.1109/BDCloud.2018.00137 SN - 2158-9178 SP - 932 EP - 939 PB - Institute of Electrical and Electronics Engineers CY - Los Alamitos ER - TY - THES A1 - Krentz, Konrad-Felix T1 - A Denial-of-Sleep-Resilient Medium Access Control Layer for IEEE 802.15.4 Networks T1 - Eine Denial-of-Sleep-Resiliente Mediumzugriffsschicht für IEEE-802.15.4-Netzwerke N2 - With the emergence of the Internet of things (IoT), plenty of battery-powered and energy-harvesting devices are being deployed to fulfill sensing and actuation tasks in a variety of application areas, such as smart homes, precision agriculture, smart cities, and industrial automation. In this context, a critical issue is that of denial-of-sleep attacks. Such attacks temporarily or permanently deprive battery-powered, energy-harvesting, or otherwise energy-constrained devices of entering energy-saving sleep modes, thereby draining their charge. At the very least, a successful denial-of-sleep attack causes a long outage of the victim device. Moreover, to put battery-powered devices back into operation, their batteries have to be replaced. This is tedious and may even be infeasible, e.g., if a battery-powered device is deployed at an inaccessible location. While the research community came up with numerous defenses against denial-of-sleep attacks, most present-day IoT protocols include no denial-of-sleep defenses at all, presumably due to a lack of awareness and unsolved integration problems. After all, despite there are many denial-of-sleep defenses, effective defenses against certain kinds of denial-of-sleep attacks are yet to be found. The overall contribution of this dissertation is to propose a denial-of-sleep-resilient medium access control (MAC) layer for IoT devices that communicate over IEEE 802.15.4 links. Internally, our MAC layer comprises two main components. The first main component is a denial-of-sleep-resilient protocol for establishing session keys among neighboring IEEE 802.15.4 nodes. The established session keys serve the dual purpose of implementing (i) basic wireless security and (ii) complementary denial-of-sleep defenses that belong to the second main component. The second main component is a denial-of-sleep-resilient MAC protocol. Notably, this MAC protocol not only incorporates novel denial-of-sleep defenses, but also state-of-the-art mechanisms for achieving low energy consumption, high throughput, and high delivery ratios. Altogether, our MAC layer resists, or at least greatly mitigates, all denial-of-sleep attacks against it we are aware of. Furthermore, our MAC layer is self-contained and thus can act as a drop-in replacement for IEEE 802.15.4-compliant MAC layers. In fact, we implemented our MAC layer in the Contiki-NG operating system, where it seamlessly integrates into an existing protocol stack. N2 - Mit dem Aufkommen des Internets der Dinge (IoT), werden immer mehr batteriebetriebene und energieerntende Geräte in diversen Anwendungsbereichen eingesetzt, etwa in der Heimautomatisierung, Präzisionslandwirtschaft, Industrieautomatisierung oder intelligenten Stadt. In diesem Kontext stellen sogenannte Denial-of-Sleep-Angriffe eine immer kritischer werdende Bedrohung dar. Solche Angriffe halten batteriebetriebene, energieerntende oder anderweitig energiebeschränkte Geräte zeitweise oder chronisch ab, in energiesparende Schlafmodi überzugehen. Erfolgreiche Denial-of-Sleep-Angriffe führen zumindest zu einer langen Ausfallzeit der betroffenen Geräte. Um betroffene batteriebetriebene Geräte wieder in Betrieb zu nehmen, müssen zudem deren Batterien gewechselt werden. Dies ist mühsam oder eventuell sogar unmöglich, z.B. wenn solche Geräte an unzugänglichen Orten installiert sind. Obwohl die Forschungsgemeinschaft bereits viele Denial-of-Sleep-Abwehrmechanismen vorgeschlagen hat, besitzen die meisten aktuellen IoT-Protokolle überhaupt keine Denial-of-Sleep-Abwehrmechanismen. Dies kann zum einen daran liegen, dass man des Problems noch nicht gewahr ist, aber zum anderen auch daran, dass viele Integrationsfragen bislang ungeklärt sind. Des Weiteren existieren bisher sowieso noch keine effektiven Abwehrmechanismen gegen bestimmte Denial-of-Sleep-Angriffe. Der Hauptbeitrag dieser Dissertation ist die Entwicklung einer Denial-of-Sleep-resilienten Mediumzugriffsschicht für IoT-Geräte, die via IEEE-802.15.4-Funkverbindungen kommunizieren. Die entwickelte Mediumzugriffsschicht besitzt zwei Hauptkomponenten. Die erste Hauptkomponente ist ein Denial-of-Sleep-resilientes Protokoll zur Etablierung von Sitzungsschlüsseln zwischen benachbarten IEEE-802.15.4-Knoten. Diese Sitzungsschlüssel dienen einerseits der grundlegenden Absicherung des Funkverkehrs und andererseits der Implementierung zusätzlicher Denial-of-Sleep-Abwehrmechanismen in der zweiten Hauptkomponente. Die zweite Hauptkomponente ist ein Denial-of-Sleep-resilientes Mediumzugriffsprotokoll. Bemerkenswert an diesem Mediumzugriffsprotokoll ist, dass es nicht nur neuartige Denial-of-Sleep-Abwehrmechanismen enthält, sondern auch dem Stand der Technik entsprechende Mechanismen zur Verringerung des Energieverbrauchs, zur Steigerung des Durchsatzes sowie zur Erhöhung der Zuverlässigkeit. Zusammenfassend widersteht bzw. mildert unsere Denial-of-Sleep-resiliente Mediumzugriffsschicht alle uns bekannten Denial-of-Sleep-Angriffe, die gegen sie gefahren werden können. Außerdem kann unsere Denial-of-Sleep-resiliente Mediumzugriffsschicht ohne Weiteres an Stelle von IEEE-802.15.4-konformen Mediumzugriffsschichten eingesetzt werden. Dies zeigen wir durch die nahtlose Integration unserer Mediumzugriffsschicht in den Netzwerk-Stack des Betriebssystems Contiki-NG. KW - medium access control KW - denial of sleep KW - internet of things KW - Mediumzugriffskontrolle KW - Schlafentzugsangriffe KW - Internet der Dinge Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-439301 ER - TY - JOUR A1 - Ihde, Sven A1 - Pufahl, Luise A1 - Völker, Maximilian A1 - Goel, Asvin A1 - Weske, Mathias T1 - A framework for modeling and executing task BT - specific resource allocations in business processes JF - Computing : archives for informatics and numerical computation N2 - As resources are valuable assets, organizations have to decide which resources to allocate to business process tasks in a way that the process is executed not only effectively but also efficiently. Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach. KW - Process Execution KW - Business Process Management KW - Resource Allocation KW - Resource Management KW - Activity-oriented Optimization Y1 - 2022 U6 - https://doi.org/10.1007/s00607-022-01093-2 SN - 0010-485X SN - 1436-5057 VL - 104 SP - 2405 EP - 2429 PB - Springer CY - Wien ER - TY - GEN A1 - Gonzalez-Lopez, Fernanda A1 - Pufahl, Luise T1 - A Landscape for Case Models T2 - Enterprise, Business-Process and Information Systems Modeling N2 - Case Management is a paradigm to support knowledge-intensive processes. The different approaches developed for modeling these types of processes tend to result in scattered models due to the low abstraction level at which the inherently complex processes are therein represented. Thus, readability and understandability is more challenging than that of traditional process models. By reviewing existing proposals in the field of process overviews and case models, this paper extends a case modeling language - the fragment-based Case Management (fCM) language - with the goal of modeling knowledge-intensive processes from a higher abstraction level - to generate a so-called fCM landscape. This proposal is empirically evaluated via an online experiment. Results indicate that interpreting an fCM landscape might be more effective and efficient than interpreting an informationally equivalent case model. KW - Case Management KW - Process landscape KW - Process map KW - Process architecture KW - Process model Y1 - 2019 SN - 978-3-030-20618-5 SN - 978-3-030-20617-8 U6 - https://doi.org/10.1007/978-3-030-20618-5_6 SN - 1865-1348 VL - 352 SP - 87 EP - 102 PB - Springer CY - Berlin ER - TY - BOOK A1 - Schneider, Sven A1 - Lambers, Leen A1 - Orejas, Fernando T1 - A logic-based incremental approach to graph repair T1 - Ein logikbasierter inkrementeller Ansatz für Graphreparatur N2 - Graph repair, restoring consistency of a graph, plays a prominent role in several areas of computer science and beyond: For example, in model-driven engineering, the abstract syntax of models is usually encoded using graphs. Flexible edit operations temporarily create inconsistent graphs not representing a valid model, thus requiring graph repair. Similarly, in graph databases—managing the storage and manipulation of graph data—updates may cause that a given database does not satisfy some integrity constraints, requiring also graph repair. We present a logic-based incremental approach to graph repair, generating a sound and complete (upon termination) overview of least-changing repairs. In our context, we formalize consistency by so-called graph conditions being equivalent to first-order logic on graphs. We present two kind of repair algorithms: State-based repair restores consistency independent of the graph update history, whereas deltabased (or incremental) repair takes this history explicitly into account. Technically, our algorithms rely on an existing model generation algorithm for graph conditions implemented in AutoGraph. Moreover, the delta-based approach uses the new concept of satisfaction (ST) trees for encoding if and how a graph satisfies a graph condition. We then demonstrate how to manipulate these STs incrementally with respect to a graph update. N2 - Die Reparatur von Graphen, die Wiederherstellung der Konsistenz eines Graphen, spielt in mehreren Bereichen der Informatik und darüber hinaus eine herausragende Rolle: Beispielsweise wird in der modellgetriebenen Konstruktion die abstrakte Syntax von Modellen in der Regel mithilfe von Graphen kodiert. Flexible Bearbeitungsvorgänge erstellen vorübergehend inkonsistente Diagramme, die kein gültiges Modell darstellen, und erfordern daher eine Reparatur des Diagramms. Auf ähnliche Weise können Aktualisierungen in Graphendatenbanken - die das Speichern und Bearbeiten von Graphendaten verwalten - dazu führen, dass eine bestimmte Datenbank einige Integritätsbeschränkungen nicht erfüllt und auch eine Graphreparatur erforderlich macht. Wir präsentieren einen logikbasierten inkrementellen Ansatz für die Graphreparatur, der eine solide und vollständige (nach Beendigung) Übersicht über die am wenigsten verändernden Reparaturen erstellt. In unserem Kontext formalisieren wir die Konsistenz mittels sogenannten Graphbedingungen die der Logik erster Ordnung in Graphen entsprechen. Wir stellen zwei Arten von Reparaturalgorithmen vor: Die zustandsbasierte Reparatur stellt die Konsistenz unabhängig vom Verlauf der Graphänderung wieder her, während die deltabasierte (oder inkrementelle) Reparatur diesen Verlauf explizit berücksichtigt. Technisch stützen sich unsere Algorithmen auf einen vorhandenen Modellgenerierungsalgorithmus für in AutoGraph implementierte Graphbedingungen. Darüber hinaus verwendet der deltabasierte Ansatz das neue Konzept der Erfüllungsbäume (STs) zum Kodieren, ob und wie ein Graph eine Graphbedingung erfüllt. Wir zeigen dann, wie diese STs in Bezug auf eine Graphaktualisierung inkrementell manipuliert werden. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 126 KW - nested graph conditions KW - graph repair KW - model repair KW - consistency restoration KW - verschachtelte Graphbedingungen KW - Graphreparatur KW - Modellreparatur KW - Konsistenzrestauration Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427517 SN - 978-3-86956-462-3 SN - 1613-5652 SN - 2191-1665 IS - 126 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - de Paula, Danielly A1 - Marx, Carolin A1 - Wolf, Ella A1 - Dremel, Christian A1 - Cormican, Kathryn A1 - Uebernickel, Falk T1 - A managerial mental model to drive innovation in the context of digital transformation JF - Industry and innovation N2 - Industry 4.0 is transforming how businesses innovate and, as a result, companies are spearheading the movement towards 'Digital Transformation'. While some scholars advocate the use of design thinking to identify new innovative behaviours, cognition experts emphasise the importance of top managers in supporting employees to develop these behaviours. However, there is a dearth of research in this domain and companies are struggling to implement the required behaviours. To address this gap, this study aims to identify and prioritise behavioural strategies conducive to design thinking to inform the creation of a managerial mental model. We identify 20 behavioural strategies from 45 interviewees with practitioners and educators and combine them with the concepts of 'paradigm-mindset-mental model' from cognition theory. The paper contributes to the body of knowledge by identifying and prioritising specific behavioural strategies to form a novel set of survival conditions aligned to the new industrial paradigm of Industry 4.0. KW - Strategic cognition KW - mental models KW - industry 4.0 KW - digital transformation KW - design thinking Y1 - 2022 U6 - https://doi.org/10.1080/13662716.2022.2072711 SN - 1366-2716 SN - 1469-8390 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Staubitz, Thomas A1 - Serth, Sebastian A1 - Thomas, Max A1 - Ebner, Martin A1 - Koschutnig-Ebner, Markus A1 - Rampelt, Florian A1 - von Stetten, Alexander A1 - Wittke, Andreas ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - A metastandard for the international exchange of MOOCs BT - the MOOChub as first prototype JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - The MOOChub is a joined web-based catalog of all relevant German and Austrian MOOC platforms that lists well over 750 Massive Open Online Courses (MOOCs). Automatically building such a catalog requires that all partners describe and publicly offer the metadata of their courses in the same way. The paper at hand presents the genesis of the idea to establish a common metadata standard and the story of its subsequent development. The result of this effort is, first, an open-licensed de-facto-standard, which is based on existing commonly used standards and second, a first prototypical platform that is using this standard: the MOOChub, which lists all courses of the involved partners. This catalog is searchable and provides a more comprehensive overview of basically all MOOCs that are offered by German and Austrian MOOC platforms. Finally, the upcoming developments to further optimize the catalog and the metadata standard are reported. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624154 SP - 147 EP - 161 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Perach, Shai A1 - Alexandron, Giora T1 - A MOOC-Based Computer Science Program for Middle School BT - Results, Challenges, and the Covid-19 Effect JF - EMOOCs 2021 N2 - In an attempt to pave the way for more extensive Computer Science Education (CSE) coverage in K-12, this research developed and made a preliminary evaluation of a blended-learning Introduction to CS program based on an academic MOOC. Using an academic MOOC that is pedagogically effective and engaging, such a program may provide teachers with disciplinary scaffolds and allow them to focus their attention on enhancing students’ learning experience and nurturing critical 21st-century skills such as self-regulated learning. As we demonstrate, this enabled us to introduce an academic level course to middle-school students. In this research, we developed the principals and initial version of such a program, targeting ninth-graders in science-track classes who learn CS as part of their standard curriculum. We found that the middle-schoolers who participated in the program achieved academic results on par with undergraduate students taking this MOOC for academic credit. Participating students also developed a more accurate perception of the essence of CS as a scientific discipline. The unplanned school closure due to the COVID19 pandemic outbreak challenged the research but underlined the advantages of such a MOOCbased blended learning program above classic pedagogy in times of global or local crises that lead to school closure. While most of the science track classes seem to stop learning CS almost entirely, and the end-of-year MoE exam was discarded, the program’s classes smoothly moved to remote learning mode, and students continued to study at a pace similar to that experienced before the school shut down. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517133 SN - 978-3-86956-512-5 VL - 2021 SP - 111 EP - 127 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Giese, Holger A1 - Henkler, Stefan A1 - Hirsch, Martin T1 - A multi-paradigm approach supporting the modular execution of reconfigurable hybrid systems N2 - Advanced mechatronic systems have to integrate existing technologies from mechanical, electrical and software engineering. They must be able to adapt their structure and behavior at runtime by reconfiguration to react flexibly to changes in the environment. Therefore, a tight integration of structural and behavioral models of the different domains is required. This integration results in complex reconfigurable hybrid systems, the execution logic of which cannot be addressed directly with existing standard modeling, simulation, and code-generation techniques. We present in this paper how our component-based approach for reconfigurable mechatronic systems, M ECHATRONIC UML, efficiently handles the complex interplay of discrete behavior and continuous behavior in a modular manner. In addition, its extension to even more flexible reconfiguration cases is presented. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 410 KW - code generation KW - hybrid systems KW - reconfigurable systems KW - simulation Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-402896 ER - TY - JOUR A1 - Navarro, Marisa A1 - Orejas, Fernando A1 - Pino, Elvira A1 - Lambers, Leen T1 - A navigational logic for reasoning about graph properties JF - Journal of logical and algebraic methods in programming N2 - Graphs play an important role in many areas of Computer Science. In particular, our work is motivated by model-driven software development and by graph databases. For this reason, it is very important to have the means to express and to reason about the properties that a given graph may satisfy. With this aim, in this paper we present a visual logic that allows us to describe graph properties, including navigational properties, i.e., properties about the paths in a graph. The logic is equipped with a deductive tableau method that we have proved to be sound and complete. KW - Graph logic KW - Algebraic methods KW - Formal modelling KW - Specification Y1 - 2021 U6 - https://doi.org/10.1016/j.jlamp.2020.100616 SN - 2352-2208 SN - 2352-2216 VL - 118 PB - Elsevier Science CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Kayem, Anne Voluntas dei Massah A1 - Meinel, Christoph A1 - Wolthusen, Stephen D. T1 - A resilient smart micro-grid architecture for resource constrained environments JF - Smart Micro-Grid Systems Security and Privacy N2 - Resource constrained smart micro-grid architectures describe a class of smart micro-grid architectures that handle communications operations over a lossy network and depend on a distributed collection of power generation and storage units. Disadvantaged communities with no or intermittent access to national power networks can benefit from such a micro-grid model by using low cost communication devices to coordinate the power generation, consumption, and storage. Furthermore, this solution is both cost-effective and environmentally-friendly. One model for such micro-grids, is for users to agree to coordinate a power sharing scheme in which individual generator owners sell excess unused power to users wanting access to power. Since the micro-grid relies on distributed renewable energy generation sources which are variable and only partly predictable, coordinating micro-grid operations with distributed algorithms is necessity for grid stability. Grid stability is crucial in retaining user trust in the dependability of the micro-grid, and user participation in the power sharing scheme, because user withdrawals can cause the grid to breakdown which is undesirable. In this chapter, we present a distributed architecture for fair power distribution and billing on microgrids. The architecture is designed to operate efficiently over a lossy communication network, which is an advantage for disadvantaged communities. We build on the architecture to discuss grid coordination notably how tasks such as metering, power resource allocation, forecasting, and scheduling can be handled. All four tasks are managed by a feedback control loop that monitors the performance and behaviour of the micro-grid, and based on historical data makes decisions to ensure the smooth operation of the grid. Finally, since lossy networks are undependable, differentiating system failures from adversarial manipulations is an important consideration for grid stability. We therefore provide a characterisation of potential adversarial models and discuss possible mitigation measures. KW - Resource constrained smart micro-grids KW - Architectures KW - Disadvantaged communities KW - Energy KW - Grid stability KW - Forecasting KW - Feedback control loop Y1 - 2018 SN - 978-3-319-91427-5 SN - 978-3-319-91426-8 U6 - https://doi.org/10.1007/978-3-319-91427-5_5 VL - 71 SP - 71 EP - 101 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Shlaka, Souhad A1 - Ouahib, Sara A1 - Berrada, Khalid ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - A retrospective feedback of MOOCS in Morocco BT - what is the best scenario for the Moroccan higher education? JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - The integration of MOOCs into the Moroccan Higher Education (MHE) took place in 2013 by developing different partnerships and projects at national and international levels. As elsewhere, the Covid-19 crisis has played an important role in accelerating distance education in MHE. However, based on our experience as both university professors and specialists in educational engineering, the effective execution of the digital transition has not yet been implemented. Thus, in this article, we present a retrospective feedback of MOOCs in Morocco, focusing on the policies taken by the government to better support the digital transition in general and MOOCs in particular. We are therefore seeking to establish an optimal scenario for the promotion of MOOCs, which emphasizes the policies to be considered, and which recalls the importance of conducting a delicate articulation taking into account four levels, namely environmental, institutional, organizational and individual. We conclude with recommendations that are inspired by the Moroccan academic contex that focus on the major role that MOOCs plays for university students and on maintaining lifelong learning. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624826 SP - 317 EP - 327 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Discher, Sören A1 - Richter, Rico A1 - Döllner, Jürgen Roland Friedrich ED - Spencer, SN T1 - A scalable webGL-based approach for visualizing massive 3D point clouds using semantics-dependent rendering techniques T2 - Web3D 2018: The 23rd International ACM Conference on 3D Web Technology N2 - 3D point cloud technology facilitates the automated and highly detailed digital acquisition of real-world environments such as assets, sites, cities, and countries; the acquired 3D point clouds represent an essential category of geodata used in a variety of geoinformation applications and systems. In this paper, we present a web-based system for the interactive and collaborative exploration and inspection of arbitrary large 3D point clouds. Our approach is based on standard WebGL on the client side and is able to render 3D point clouds with billions of points. It uses spatial data structures and level-of-detail representations to manage the 3D point cloud data and to deploy out-of-core and web-based rendering concepts. By providing functionality for both, thin-client and thick-client applications, the system scales for client devices that are vastly different in computing capabilities. Different 3D point-based rendering techniques and post-processing effects are provided to enable task-specific and data-specific filtering and highlighting, e.g., based on per-point surface categories or temporal information. A set of interaction techniques allows users to collaboratively work with the data, e.g., by measuring distances and areas, by annotating, or by selecting and extracting data subsets. Additional value is provided by the system's ability to display additional, context-providing geodata alongside 3D point clouds and to integrate task-specific processing and analysis operations. We have evaluated the presented techniques and the prototype system with different data sets from aerial, mobile, and terrestrial acquisition campaigns with up to 120 billion points to show their practicality and feasibility. KW - 3D Point Clouds KW - web-based rendering KW - point-based rendering Y1 - 2018 SN - 978-1-4503-5800-2 U6 - https://doi.org/10.1145/3208806.3208816 SP - 1 EP - 9 PB - Association for Computing Machinery CY - New York ER - TY - THES A1 - Buschmann, Stefan T1 - A software framework for GPU-based geo-temporal visualization techniques T1 - Ein Software-Framework für GPU-basierte räumlich-zeitliche Visualisierungstechniken N2 - Räumlich-zeitliche Daten sind Daten, welche sowohl einen Raum- als auch einen Zeitbezug aufweisen. So können beispielsweise Zeitreihen von Geodaten, thematische Karten die sich über die Zeit verändern, oder Bewegungsaufzeichnungen von sich bewegenden Objekten als räumlich-zeitliche Daten aufgefasst werden. In der heutigen automatisierten Welt gibt es eine wachsende Anzahl von Datenquellen, die beständig räumlich-zeitliche Daten generieren. Hierzu gehören beispielsweise Verkehrsüberwachungssysteme, die Bewegungsdaten von Menschen oder Fahrzeugen aufzeichnen, Fernerkundungssysteme, welche regelmäßig unsere Umgebung scannen und digitale Abbilder wie z.B. Stadt- und Landschaftsmodelle erzeugen, sowie Sensornetzwerke in unterschiedlichsten Anwendungsgebieten, wie z.B. der Logistik, der Verhaltensforschung von Tieren, oder der Klimaforschung. Zur Analyse räumlich-zeitlicher Daten werden neben der automatischen Analyse mittels statistischer Methoden und Data-Mining auch explorative Methoden angewendet, welche auf der interaktiven Visualisierung der Daten beruhen. Diese Methode der Analyse basiert darauf, dass Anwender in Form interaktiver Visualisierung die Daten explorieren können, wodurch die menschliche Wahrnehmung sowie das Wissen der User genutzt werden, um Muster zu erkennen und dadurch einen Einblick in die Daten zu erlangen. Diese Arbeit beschreibt ein Software-Framework für die Visualisierung räumlich-zeitlicher Daten, welches GPU-basierte Techniken beinhaltet, um eine interaktive Visualisierung und Exploration großer räumlich-zeitlicher Datensätze zu ermöglichen. Die entwickelten Techniken umfassen Datenhaltung, Prozessierung und Rendering und ermöglichen es, große Datenmengen in Echtzeit zu prozessieren und zu visualisieren. Die Hauptbeiträge der Arbeit umfassen: - Konzept und Implementierung einer GPU-zentrierten Visualisierungspipeline. Die beschriebenen Techniken basieren auf dem Konzept einer GPU-zentrierten Visualisierungspipeline, in welcher alle Stufen -- Prozessierung,Mapping, Rendering -- auf der GPU ausgeführt werden. Bei diesem Konzept werden die räumlich-zeitlichen Daten direkt im GPU-Speicher abgelegt. Während des Rendering-Prozesses werden dann mittels Shader-Programmen die Daten prozessiert, gefiltert, ein Mapping auf visuelle Attribute vorgenommen, und schließlich die Geometrien für die Visualisierung erzeugt. Datenprozessierung, Filtering und Mapping können daher in Echtzeit ausgeführt werden. Dies ermöglicht es Usern, die Mapping-Parameter sowie den gesamten Visualisierungsprozess interaktiv zu steuern und zu kontrollieren. - Interaktive Visualisierung attributierter 3D-Trajektorien. Es wurde eine Visualisierungsmethode für die interaktive Exploration einer großen Anzahl von 3D Bewegungstrajektorien entwickelt. Die Trajektorien werden dabei innerhalb einer virtuellen geographischen Umgebung in Form von einfachen Geometrien, wie Linien, Bändern, Kugeln oder Röhren dargestellt. Durch interaktives Mapping können Attributwerte der Trajektorien oder einzelner Messpunkte auf visuelle Eigenschaften abgebildet werden. Hierzu stehen Form, Höhe, Größe, Farbe, Textur, sowie Animation zur Verfügung. Mithilfe dieses dynamischen Mappings wurden außerdem verschiedene Visualisierungsmethoden implementiert, wie z.B. eine Focus+Context-Visualisierung von Trajektorien mithilfe von interaktiven Dichtekarten, sowie einer Space-Time-Cube-Visualisierung zur Darstellung des zeitlichen Ablaufs einzelner Bewegungen. - Interaktive Visualisierung geographischer Netzwerke. Es wurde eine Visualisierungsmethode zur interaktiven Exploration geo-referenzierter Netzwerke entwickelt, welche die Visualisierung von Netzwerken mit einer großen Anzahl von Knoten und Kanten ermöglicht. Um die Analyse von Netzwerken verschiedener Größen und in unterschiedlichen Kontexten zu ermöglichen, stehen mehrere virtuelle geographische Umgebungen zur Verfügung, wie bspw. ein virtueller 3D-Globus, als auch 2D-Karten mit unterschiedlichen geographischen Projektionen. Zur interaktiven Analyse dieser Netzwerke stehen interaktive Tools wie Filterung, Mapping und Selektion zur Verfügung. Des weiteren wurden Visualisierungsmethoden für verschiedene Arten von Netzwerken, wie z.B. 3D-Netzwerke und zeitlich veränderliche Netzwerke, implementiert. Zur Demonstration des Konzeptes wurden interaktive Tools für zwei unterschiedliche Anwendungsfälle entwickelt. Das erste beinhaltet die Visualisierung attributierter 3D-Trajektorien, welche die Bewegungen von Flugzeugen um einen Flughafen beschreiben. Es ermöglicht Nutzern, die Trajektorien von ankommenden und startenden Flugzeugen über den Zeitraum eines Monats interaktiv zu explorieren und zu analysieren. Durch Verwendung der interaktiven Visualisierungsmethoden für 3D-Trajektorien und interaktiven Dichtekarten können Einblicke in die Daten gewonnen werden, wie beispielsweise häufig genutzte Flugkorridore, typische sowie untypische Bewegungsmuster, oder ungewöhnliche Vorkommnisse wie Fehlanflüge. Der zweite Anwendungsfall beinhaltet die Visualisierung von Klimanetzwerken, welche geographischen Netzwerken in der Klimaforschung darstellen. Klimanetzwerke repräsentieren die Dynamiken im Klimasystem durch eine Netzwerkstruktur, die die statistische Beziehungen zwischen Orten beschreiben. Das entwickelte Tool ermöglicht es Analysten, diese großen Netzwerke interaktiv zu explorieren und dadurch die Struktur des Netzwerks zu analysieren und mit den geographischen Daten in Beziehung zu setzen. Interaktive Filterung und Selektion ermöglichen es, Muster in den Daten zu identifizieren, und so bspw. Cluster in der Netzwerkstruktur oder Strömungsmuster zu erkennen. N2 - Spatio-temporal data denotes a category of data that contains spatial as well as temporal components. For example, time-series of geo-data, thematic maps that change over time, or tracking data of moving entities can be interpreted as spatio-temporal data. In today's automated world, an increasing number of data sources exist, which constantly generate spatio-temporal data. This includes for example traffic surveillance systems, which gather movement data about human or vehicle movements, remote-sensing systems, which frequently scan our surroundings and produce digital representations of cities and landscapes, as well as sensor networks in different domains, such as logistics, animal behavior study, or climate research. For the analysis of spatio-temporal data, in addition to automatic statistical and data mining methods, exploratory analysis methods are employed, which are based on interactive visualization. These analysis methods let users explore a data set by interactively manipulating a visualization, thereby employing the human cognitive system and knowledge of the users to find patterns and gain insight into the data. This thesis describes a software framework for the visualization of spatio-temporal data, which consists of GPU-based techniques to enable the interactive visualization and exploration of large spatio-temporal data sets. The developed techniques include data management, processing, and rendering, facilitating real-time processing and visualization of large geo-temporal data sets. It includes three main contributions: - Concept and Implementation of a GPU-Based Visualization Pipeline. The developed visualization methods are based on the concept of a GPU-based visualization pipeline, in which all steps -- processing, mapping, and rendering -- are implemented on the GPU. With this concept, spatio-temporal data is represented directly in GPU memory, using shader programs to process and filter the data, apply mappings to visual properties, and finally generate the geometric representations for a visualization during the rendering process. Data processing, filtering, and mapping are thereby executed in real-time, enabling dynamic control over the mapping and a visualization process which can be controlled interactively by a user. - Attributed 3D Trajectory Visualization. A visualization method has been developed for the interactive exploration of large numbers of 3D movement trajectories. The trajectories are visualized in a virtual geographic environment, supporting basic geometries such as lines, ribbons, spheres, or tubes. Interactive mapping can be applied to visualize the values of per-node or per-trajectory attributes, supporting shape, height, size, color, texturing, and animation as visual properties. Using the dynamic mapping system, several kind of visualization methods have been implemented, such as focus+context visualization of trajectories using interactive density maps, and space-time cube visualization to focus on the temporal aspects of individual movements. - Geographic Network Visualization. A method for the interactive exploration of geo-referenced networks has been developed, which enables the visualization of large numbers of nodes and edges in a geographic context. Several geographic environments are supported, such as a 3D globe, as well as 2D maps using different map projections, to enable the analysis of networks in different contexts and scales. Interactive filtering, mapping, and selection can be applied to analyze these geographic networks, and visualization methods for specific types of networks, such as coupled 3D networks or temporal networks have been implemented. As a demonstration of the developed visualization concepts, interactive visualization tools for two distinct use cases have been developed. The first contains the visualization of attributed 3D movement trajectories of airplanes around an airport. It allows users to explore and analyze the trajectories of approaching and departing aircrafts, which have been recorded over the period of a month. By applying the interactive visualization methods for trajectory visualization and interactive density maps, analysts can derive insight from the data, such as common flight paths, regular and irregular patterns, or uncommon incidents such as missed approaches on the airport. The second use case involves the visualization of climate networks, which are geographic networks in the climate research domain. They represent the dynamics of the climate system using a network structure that expresses statistical interrelationships between different regions. The interactive tool allows climate analysts to explore these large networks, analyzing the network's structure and relating it to the geographic background. Interactive filtering and selection enables them to find patterns in the climate data and identify e.g. clusters in the networks or flow patterns. KW - computer graphics KW - visualization KW - visual analytics KW - Computergrafik KW - Visualisierung KW - Visual Analytics Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-443406 ER - TY - JOUR A1 - Krestel, Ralf A1 - Chikkamath, Renukswamy A1 - Hewel, Christoph A1 - Risch, Julian T1 - A survey on deep learning for patent analysis JF - World patent information N2 - Patent document collections are an immense source of knowledge for research and innovation communities worldwide. The rapid growth of the number of patent documents poses an enormous challenge for retrieving and analyzing information from this source in an effective manner. Based on deep learning methods for natural language processing, novel approaches have been developed in the field of patent analysis. The goal of these approaches is to reduce costs by automating tasks that previously only domain experts could solve. In this article, we provide a comprehensive survey of the application of deep learning for patent analysis. We summarize the state-of-the-art techniques and describe how they are applied to various tasks in the patent domain. In a detailed discussion, we categorize 40 papers based on the dataset, the representation, and the deep learning architecture that were used, as well as the patent analysis task that was targeted. With our survey, we aim to foster future research at the intersection of patent analysis and deep learning and we conclude by listing promising paths for future work. KW - deep learning KW - patent analysis KW - text mining KW - natural language processing Y1 - 2021 U6 - https://doi.org/10.1016/j.wpi.2021.102035 SN - 0172-2190 SN - 1874-690X VL - 65 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Richly, Keven T1 - A survey on trajectory data management for hybrid transactional and analytical workloads T2 - IEEE International Conference on Big Data (Big Data) N2 - Rapid advances in location-acquisition technologies have led to large amounts of trajectory data. This data is the foundation for a broad spectrum of services driven and improved by trajectory data mining. However, for hybrid transactional and analytical workloads, the storing and processing of rapidly accumulated trajectory data is a non-trivial task. In this paper, we present a detailed survey about state-of-the-art trajectory data management systems. To determine the relevant aspects and requirements for such systems, we developed a trajectory data mining framework, which summarizes the different steps in the trajectory data mining process. Based on the derived requirements, we analyze different concepts to store, compress, index, and process spatio-temporal data. There are various trajectory management systems, which are optimized for scalability, data footprint reduction, elasticity, or query performance. To get a comprehensive overview, we describe and compare different exciting systems. Additionally, the observed similarities in the general structure of different systems are consolidated in a general blueprint of trajectory management systems. KW - Trajectory Data Management KW - Spatio-Temporal Data KW - Survey Y1 - 2019 SN - 978-1-5386-5035-6 U6 - https://doi.org/10.1109/BigData.2018.8622394 SN - 2639-1589 SP - 562 EP - 569 PB - IEEE CY - New York ER - TY - THES A1 - Kraus, Sara Milena T1 - A Systems Medicine approach for heart valve diseases BT - addressing the proteomic landscape and differential expression software N2 - In Systems Medicine, in addition to high-throughput molecular data (*omics), the wealth of clinical characterization plays a major role in the overall understanding of a disease. Unique problems and challenges arise from the heterogeneity of data and require new solutions to software and analysis methods. The SMART and EurValve studies establish a Systems Medicine approach to valvular heart disease -- the primary cause of subsequent heart failure. With the aim to ascertain a holistic understanding, different *omics as well as the clinical picture of patients with aortic stenosis (AS) and mitral regurgitation (MR) are collected. Our task within the SMART consortium was to develop an IT platform for Systems Medicine as a basis for data storage, processing, and analysis as a prerequisite for collaborative research. Based on this platform, this thesis deals on the one hand with the transfer of the used Systems Biology methods to their use in the Systems Medicine context and on the other hand with the clinical and biomolecular differences of the two heart valve diseases. To advance differential expression/abundance (DE/DA) analysis software for use in Systems Medicine, we state 21 general software requirements and features of automated DE/DA software, including a novel concept for the simple formulation of experimental designs that can represent complex hypotheses, such as comparison of multiple experimental groups, and demonstrate our handling of the wealth of clinical data in two research applications DEAME and Eatomics. In user interviews, we show that novice users are empowered to formulate and test their multiple DE hypotheses based on clinical phenotype. Furthermore, we describe insights into users' general impression and expectation of the software's performance and show their intention to continue using the software for their work in the future. Both research applications cover most of the features of existing tools or even extend them, especially with respect to complex experimental designs. Eatomics is freely available to the research community as a user-friendly R Shiny application. Eatomics continued to help drive the collaborative analysis and interpretation of the proteomic profile of 75 human left myocardial tissue samples from the SMART and EurValve studies. Here, we investigate molecular changes within the two most common types of valvular heart disease: aortic valve stenosis (AS) and mitral valve regurgitation (MR). Through DE/DA analyses, we explore shared and disease-specific protein alterations, particularly signatures that could only be found in the sex-stratified analysis. In addition, we relate changes in the myocardial proteome to parameters from clinical imaging. We find comparable cardiac hypertrophy but differences in ventricular size, the extent of fibrosis, and cardiac function. We find that AS and MR show many shared remodeling effects, the most prominent of which is an increase in the extracellular matrix and a decrease in metabolism. Both effects are stronger in AS. In muscle and cytoskeletal adaptations, we see a greater increase in mechanotransduction in AS and an increase in cortical cytoskeleton in MR. The decrease in proteostasis proteins is mainly attributable to the signature of female patients with AS. We also find relevant therapeutic targets. In addition to the new findings, our work confirms several concepts from animal and heart failure studies by providing the largest collection of human tissue from in vivo collected biopsies to date. Our dataset contributing a resource for isoform-specific protein expression in two of the most common valvular heart diseases. Apart from the general proteomic landscape, we demonstrate the added value of the dataset by showing proteomic and transcriptomic evidence for increased expression of the SARS-CoV-2- receptor at pressure load but not at volume load in the left ventricle and also provide the basis of a newly developed metabolic model of the heart. N2 - In der Systemmedizin spielt zusätzlich zu den molekularen Hochdurchsatzdaten (*omics) die Fülle an klinischer Charakterisierung eine große Rolle im Gesamtverständnis einer Krankheit. Hieraus ergeben sich Probleme und Herausforderungen unter anderem in Bezug auf Softwarelösungen und Analysemethoden. Die SMART- und EurValve-Studien etablieren einen systemmedizinischen Ansatz für Herzklappenerkrankungen -- die Hauptursache für eine spätere Herzinsuffizienz. Mit dem Ziel ein ganzheitliches Verständnis zu etablieren, werden verschiedene *omics sowie das klinische Bild von Patienten mit Aortenstenosen (AS) und Mitralklappeninsuffizienz (MR) erhoben. Unsere Aufgabe innerhalb des SMART Konsortiums bestand in der Entwicklung einer IT-Plattform für Systemmedizin als Grundlage für die Speicherung, Verarbeitung und Analyse von Daten als Voraussetzung für gemeinsame Forschung. Ausgehend von dieser Plattform beschäftigt sich diese Arbeit einerseits mit dem Transfer der genutzten systembiologischen Methoden hin zu einer Nutzung im systemmedizinischen Kontext und andererseits mit den klinischen und biomolekularen Unterschieden der beiden Herzklappenerkrankungen. Um die Analysesoftware für differenzielle Expression/Abundanz, eine häufig genutzte Methode der System Biologie, für die Nutzung in der Systemmedizin voranzutreiben, erarbeiten wir 21 allgemeine Softwareanforderungen und Funktionen einer automatisierten DE/DA Software. Darunter ist ein neuartiges Konzept für die einfache Formulierung experimenteller Designs, die auch komplexe Hypothesen wie den Vergleich mehrerer experimenteller Gruppen abbilden können und demonstrieren unseren Umgang mit der Fülle klinischer Daten in zwei Forschungsanwendungen -- DEAME und Eatomics. In Nutzertests zeigen wir, dass Nutzer befähigt werden, ihre vielfältigen Hypothesen zur differenziellen Expression basierend auf dem klinischen Phänotyp zu formulieren und zu testen, auch ohne einen dedizierten Hintergrund in Bioinformatik. Darüber hinaus beschreiben wir Einblicke in den allgemeinen Eindruck der Nutzer, ihrer Erwartung an die Leistung der Software und zeigen ihre Absicht, die Software auch in der Zukunft für ihre Arbeit zu nutzen. Beide Forschungsanwendungen decken die meisten Funktionen bestehender Tools ab oder erweitern sie sogar, insbesondere im Hinblick auf komplexe experimentelle Designs. Eatomics steht der Forschungsgemeinschaft als benutzerfreundliche R Shiny-Anwendung frei zur Verfügung. \textit{Eatomics} hat weiterhin dazu beigetragen, die gemeinsame Analyse und Interpretation des Proteomprofils von 75 menschlichen linken Myokardgewebeproben aus den SMART- und EurValve-Studien voran zu treiben. Hier untersuchen wir die molekularen Veränderungen innerhalb der beiden häufigsten Arten von Herzklappenerkrankungen: AS und MR. Durch DE/DA Analysen erarbeiten wir gemeinsame und krankheitsspezifische Proteinveränderungen, insbesondere Signaturen, die nur in einer geschlechtsstratifizierten Analyse gefunden werden konnten. Darüber hinaus beziehen wir Veränderungen des Myokardproteoms auf Parameter aus der klinischen Bildgebung. Wir finden eine vergleichbare kardiale Hypertrophie, aber Unterschiede in der Ventrikelgröße, dem Ausmaß der Fibrose und der kardialen Funktion. Wir stellen fest, dass AS und MR viele gemeinsame Remodelling-Effekte zeigen, von denen die wichtigsten die Zunahme der extrazellulären Matrix und eine Abnahme des Metabolismus sind. Beide Effekte sind bei AS stärker. Zusätzlich zeigt sich eine größere Variabilität zwischen den einzelnen Patienten mit AS. Bei Muskel- und Zytoskelettanpassungen sehen wir einen stärkeren Anstieg der Mechanotransduktion bei AS und einen Anstieg des kortikalen Zytoskeletts bei MR. Die Abnahme von Proteinen der Proteostase ist vor allem der Signatur von weiblichen Patienten mit AS zuzuschreiben. Außerdem finden wir therapierelevante Proteinveränderungen. Zusätzlich zu den neuen Erkenntnissen bestätigt unsere Arbeit mehrere Konzepte aus Tierstudien und Studien zu Herzversagen durch die bislang größte Kollektion von humanem Gewebe aus in vivo Biopsien. Mit unserem Datensatz stellen wir eine Ressource für die isoformspezifische Proteinexpression bei zwei der häufigsten Herzklappenerkrankungen zur Verfügung. Abgesehen von der allgemeinen Proteomlandschaft zeigen wir den Mehrwert des Datensatzes, indem wir proteomische und transkriptomische Beweise für eine erhöhte Expression des SARS-CoV-2- Rezeptors bei Drucklast, jedoch nicht bei Volumenlast im linken Ventrikel aufzeigen und außerdem die Grundlage eines neu entwickelten metabolischen Modells des Herzens liefern. KW - Systems Medicine KW - Systemmedizin KW - Proteomics KW - Proteom KW - Heart Valve Diseases KW - Herzklappenerkrankungen KW - Differential Expression Analysis KW - Software KW - Software Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-522266 ER - TY - JOUR A1 - Scheibel, Willy A1 - Trapp, Matthias A1 - Limberger, Daniel A1 - Döllner, Jürgen Roland Friedrich T1 - A taxonomy of treemap visualization techniques JF - Science and Technology Publications N2 - A treemap is a visualization that has been specifically designed to facilitate the exploration of tree-structured data and, more general, hierarchically structured data. The family of visualization techniques that use a visual metaphor for parent-child relationships based “on the property of containment” (Johnson, 1993) is commonly referred to as treemaps. However, as the number of variations of treemaps grows, it becomes increasingly important to distinguish clearly between techniques and their specific characteristics. This paper proposes to discern between Space-filling Treemap TS, Containment Treemap TC, Implicit Edge Representation Tree TIE, and Mapped Tree TMT for classification of hierarchy visualization techniques and highlights their respective properties. This taxonomy is created as a hyponymy, i.e., its classes have an is-a relationship to one another: TS TC TIE TMT. With this proposal, we intend to stimulate a discussion on a more unambiguous classification of treemaps and, furthermore, broaden what is understood by the concept of treemap itself. KW - Treemaps KW - Taxonomy Y1 - 2020 PB - Springer CY - Berlin ER - TY - GEN A1 - Scheibel, Willy A1 - Trapp, Matthias A1 - Limberger, Daniel A1 - Döllner, Jürgen Roland Friedrich T1 - A taxonomy of treemap visualization techniques T2 - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - A treemap is a visualization that has been specifically designed to facilitate the exploration of tree-structured data and, more general, hierarchically structured data. The family of visualization techniques that use a visual metaphor for parent-child relationships based “on the property of containment” (Johnson, 1993) is commonly referred to as treemaps. However, as the number of variations of treemaps grows, it becomes increasingly important to distinguish clearly between techniques and their specific characteristics. This paper proposes to discern between Space-filling Treemap TS, Containment Treemap TC, Implicit Edge Representation Tree TIE, and Mapped Tree TMT for classification of hierarchy visualization techniques and highlights their respective properties. This taxonomy is created as a hyponymy, i.e., its classes have an is-a relationship to one another: TS TC TIE TMT. With this proposal, we intend to stimulate a discussion on a more unambiguous classification of treemaps and, furthermore, broaden what is understood by the concept of treemap itself. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 8 KW - treemaps KW - taxonomy Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-524693 IS - 8 ER - TY - JOUR A1 - Nohr, Magnus A1 - Haugsbakken, Halvdan ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - A taxonomy of video genres as a scaffolding strategy for video making in education JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - This research paper aims to introduce a novel practitioner-oriented and research-based taxonomy of video genres. This taxonomy can serve as a scaffolding strategy to support educators throughout the entire educational system in creating videos for pedagogical purposes. A taxonomy of video genres is essential as videos are highly valued resources among learners. Although the use of videos in education has been extensively researched and well-documented in systematic research reviews, gaps remain in the literature. Predominantly, researchers employ sophisticated quantitative methods and similar approaches to measure the performance of videos. This trend has led to the emergence of a strong learning analytics research tradition with its embedded literature. This body of research includes analysis of performance of videos in online courses such as Massive Open Online Courses (MOOCs). Surprisingly, this same literature is limited in terms of research outlining approaches to designing and creating educational videos, which applies to both video-based learning and online courses. This issue results in a knowledge gap, highlighting the need for developing pedagogical tools and strategies for video making. These can be found in frameworks, guidelines, and taxonomies, which can serve as scaffolding strategies. In contrast, there appears to be very few frameworks available for designing and creating videos for pedagogica purposes, apart from a few well-known frameworks. In this regard, this research paper proposes a novel taxonomy of video genres that educators can utilize when creating videos intended for use in either video-based learning environments or online courses. To create this taxonomy, a large number of videos from online courses were collected and analyzed using a mixed-method research design approach. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624294 SP - 201 EP - 220 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Perscheid, Cindy A1 - Faber, Lukas A1 - Kraus, Milena A1 - Arndt, Paul A1 - Janke, Michael A1 - Rehfeldt, Sebastian A1 - Schubotz, Antje A1 - Slosarek, Tamara A1 - Uflacker, Matthias T1 - A tissue-aware gene selection approach for analyzing multi-tissue gene expression data T2 - 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) N2 - High-throughput RNA sequencing (RNAseq) produces large data sets containing expression levels of thousands of genes. The analysis of RNAseq data leads to a better understanding of gene functions and interactions, which eventually helps to study diseases like cancer and develop effective treatments. Large-scale RNAseq expression studies on cancer comprise samples from multiple cancer types and aim to identify their distinct molecular characteristics. Analyzing samples from different cancer types implies analyzing samples from different tissue origin. Such multi-tissue RNAseq data sets require a meaningful analysis that accounts for the inherent tissue-related bias: The identified characteristics must not originate from the differences in tissue types, but from the actual differences in cancer types. However, current analysis procedures do not incorporate that aspect. As a result, we propose to integrate a tissue-awareness into the analysis of multi-tissue RNAseq data. We introduce an extension for gene selection that provides a tissue-wise context for every gene and can be flexibly combined with any existing gene selection approach. We suggest to expand conventional evaluation by additional metrics that are sensitive to the tissue-related bias. Evaluations show that especially low complexity gene selection approaches profit from introducing tissue-awareness. KW - RNAseq KW - gene selection KW - tissue-awareness KW - TCGA KW - GTEx Y1 - 2018 SN - 978-1-5386-5488-0 U6 - https://doi.org/10.1109/BIBM.2018.8621189 SN - 2156-1125 SN - 2156-1133 SP - 2159 EP - 2166 PB - IEEE CY - New York ER - TY - THES A1 - Katzmann, Maximilian T1 - About the analysis of algorithms on networks with underlying hyperbolic geometry T1 - Über die Analyse von Algorithmen auf Netzwerken mit zugrundeliegender hyperbolischer Geometrie N2 - Many complex systems that we encounter in the world can be formalized using networks. Consequently, they have been in the focus of computer science for decades, where algorithms are developed to understand and utilize these systems. Surprisingly, our theoretical understanding of these algorithms and their behavior in practice often diverge significantly. In fact, they tend to perform much better on real-world networks than one would expect when considering the theoretical worst-case bounds. One way of capturing this discrepancy is the average-case analysis, where the idea is to acknowledge the differences between practical and worst-case instances by focusing on networks whose properties match those of real graphs. Recent observations indicate that good representations of real-world networks are obtained by assuming that a network has an underlying hyperbolic geometry. In this thesis, we demonstrate that the connection between networks and hyperbolic space can be utilized as a powerful tool for average-case analysis. To this end, we first introduce strongly hyperbolic unit disk graphs and identify the famous hyperbolic random graph model as a special case of them. We then consider four problems where recent empirical results highlight a gap between theory and practice and use hyperbolic graph models to explain these phenomena theoretically. First, we develop a routing scheme, used to forward information in a network, and analyze its efficiency on strongly hyperbolic unit disk graphs. For the special case of hyperbolic random graphs, our algorithm beats existing performance lower bounds. Afterwards, we use the hyperbolic random graph model to theoretically explain empirical observations about the performance of the bidirectional breadth-first search. Finally, we develop algorithms for computing optimal and nearly optimal vertex covers (problems known to be NP-hard) and show that, on hyperbolic random graphs, they run in polynomial and quasi-linear time, respectively. Our theoretical analyses reveal interesting properties of hyperbolic random graphs and our empirical studies present evidence that these properties, as well as our algorithmic improvements translate back into practice. N2 - Viele komplexe Systeme mit denen wir tagtäglich zu tun haben, können mit Hilfe von Netzwerken beschrieben werden, welche daher schon jahrzehntelang im Fokus der Informatik stehen. Dort werden Algorithmen entwickelt, um diese Systeme besser verstehen und nutzen zu können. Überraschenderweise unterscheidet sich unsere theoretische Vorstellung dieser Algorithmen jedoch oft immens von derem praktischen Verhalten. Tatsächlich neigen sie dazu auf echten Netzwerken viel effizienter zu sein, als man im schlimmsten Fall erwarten würde. Eine Möglichkeit diese Diskrepanz zu erfassen ist die Average-Case Analyse bei der man die Unterschiede zwischen echten Instanzen und dem schlimmsten Fall ausnutzt, indem ausschließlich Netzwerke betrachtet werden, deren Eigenschaften die von echten Graphen gut abbilden. Jüngste Beobachtungen zeigen, dass gute Abbildungen entstehen, wenn man annimmt, dass einem Netzwerk eine hyperbolische Geometrie zugrunde liegt. In dieser Arbeit wird demonstriert, dass hyperbolische Netzwerke als mächtiges Werkzeug der Average-Case Analyse dienen können. Dazu werden stark-hyperbolische Unit-Disk-Graphen eingeführt und die bekannten hyperbolischen Zufallsgraphen als ein Sonderfall dieser identifiziert. Anschließend werden auf diesen Modellen vier Probleme analysiert, um Resultate vorangegangener Experimente theoretisch zu erklären, die eine Diskrepanz zwischen Theorie und Praxis aufzeigten. Zuerst wird ein Routing Schema zum Transport von Nachrichten entwickelt und dessen Effizienz auf stark-hyperbolischen Unit-Disk-Graphen untersucht. Allgemeingültige Effizienzschranken können so auf hyperbolischen Zufallsgraphen unterboten werden. Anschließend wird das hyperbolische Zufallsgraphenmodell verwendet, um praktische Beobachtungen der bidirektionalen Breitensuche theoretisch zu erklären und es werden Algorithmen entwickelt, um optimale und nahezu optimale Knotenüberdeckungen zu berechnen (NP-schwer), deren Laufzeit auf diesen Graphen jeweils polynomiell und quasi-linear ist. In den Analysen werden neue Eigenschaften von hyperbolischen Zufallsgraphen aufgedeckt und empirisch gezeigt, dass sich diese sowie die algorithmischen Verbesserungen auch auf echten Netzwerken nachweisen lassen. KW - graph theory KW - hyperbolic geometry KW - average-case analysis KW - Average-Case Analyse KW - Graphentheorie KW - hyperbolische Geometrie Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-582965 ER - TY - RPRT A1 - Döllner, Jürgen Roland Friedrich A1 - Friedrich, Tobias A1 - Arnrich, Bert A1 - Hirschfeld, Robert A1 - Lippert, Christoph A1 - Meinel, Christoph T1 - Abschlussbericht KI-Labor ITSE T1 - Final report "AI Lab ITSE" BT - KI-Labor für Methodik, Technik und Ausbildung in der IT-Systemtechnik N2 - Der Abschlussbericht beschreibt Aufgaben und Ergebnisse des KI-Labors "ITSE". Gegenstand des KI-Labors bildeten Methodik, Technik und Ausbildung in der IT-Systemtechnik zur Analyse, Planung und Konstruktion KI-basierter, komplexer IT-Systeme. N2 - Final Report on the "AI Lab ITSE" dedicated to Methodology, Technology and Education of AI in IT-Systems Engineering. KW - Abschlussbericht KW - KI-Labor KW - final report KW - AI Lab Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-578604 ER - TY - JOUR A1 - Yousfi, Alaaeddine A1 - Batoulis, Kimon A1 - Weske, Mathias T1 - Achieving Business Process Improvement via Ubiquitous Decision-Aware Business Processes JF - ACM Transactions on Internet Technology N2 - Business process improvement is an endless challenge for many organizations. As long as there is a process, it must he improved. Nowadays, improvement initiatives are driven by professionals. This is no longer practical because people cannot perceive the enormous data of current business environments. Here, we introduce ubiquitous decision-aware business processes. They pervade the physical space, analyze the ever-changing environments, and make decisions accordingly. We explain how they can be built and used for improvement. Our approach can be a valuable improvement option to alleviate the workload of participants by helping focus on the crucial rather than the menial tasks. KW - Business process improvement KW - ubiquitous decision-aware business process KW - ubiquitous decisions KW - context KW - uBPMN KW - DMN Y1 - 2019 U6 - https://doi.org/10.1145/3298986 SN - 1533-5399 SN - 1557-6051 VL - 19 IS - 1 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Limanowski, Jakub A1 - Lopes, Pedro A1 - Keck, Janis A1 - Baudisch, Patrick A1 - Friston, Karl A1 - Blankenburg, Felix T1 - Action-dependent processing of touch in the human parietal operculum and posterior insula JF - Cerebral Cortex N2 - Somatosensory input generated by one's actions (i.e., self-initiated body movements) is generally attenuated. Conversely, externally caused somatosensory input is enhanced, for example, during active touch and the haptic exploration of objects. Here, we used functional magnetic resonance imaging (fMRI) to ask how the brain accomplishes this delicate weighting of self-generated versus externally caused somatosensory components. Finger movements were either self-generated by our participants or induced by functional electrical stimulation (FES) of the same muscles. During half of the trials, electrotactile impulses were administered when the (actively or passively) moving finger reached a predefined flexion threshold. fMRI revealed an interaction effect in the contralateral posterior insular cortex (pIC), which responded more strongly to touch during self-generated than during FES-induced movements. A network analysis via dynamic causal modeling revealed that connectivity from the secondary somatosensory cortex via the pIC to the supplementary motor area was generally attenuated during self-generated relative to FES-induced movements-yet specifically enhanced by touch received during self-generated, but not FES-induced movements. Together, these results suggest a crucial role of the parietal operculum and the posterior insula in differentiating self-generated from externally caused somatosensory information received from one's moving limb. KW - active touch KW - dynamic causal modeling KW - insula KW - parietal operculum KW - somatosensation Y1 - 2019 U6 - https://doi.org/10.1093/cercor/bhz111 SN - 1047-3211 SN - 1460-2199 VL - 30 IS - 2 SP - 607 EP - 617 PB - Oxford University Press CY - Oxford ER - TY - THES A1 - Grütze, Toni T1 - Adding value to text with user-generated content N2 - In recent years, the ever-growing amount of documents on the Web as well as in closed systems for private or business contexts led to a considerable increase of valuable textual information about topics, events, and entities. It is a truism that the majority of information (i.e., business-relevant data) is only available in unstructured textual form. The text mining research field comprises various practice areas that have the common goal of harvesting high-quality information from textual data. These information help addressing users' information needs. In this thesis, we utilize the knowledge represented in user-generated content (UGC) originating from various social media services to improve text mining results. These social media platforms provide a plethora of information with varying focuses. In many cases, an essential feature of such platforms is to share relevant content with a peer group. Thus, the data exchanged in these communities tend to be focused on the interests of the user base. The popularity of social media services is growing continuously and the inherent knowledge is available to be utilized. We show that this knowledge can be used for three different tasks. Initially, we demonstrate that when searching persons with ambiguous names, the information from Wikipedia can be bootstrapped to group web search results according to the individuals occurring in the documents. We introduce two models and different means to handle persons missing in the UGC source. We show that the proposed approaches outperform traditional algorithms for search result clustering. Secondly, we discuss how the categorization of texts according to continuously changing community-generated folksonomies helps users to identify new information related to their interests. We specifically target temporal changes in the UGC and show how they influence the quality of different tag recommendation approaches. Finally, we introduce an algorithm to attempt the entity linking problem, a necessity for harvesting entity knowledge from large text collections. The goal is the linkage of mentions within the documents with their real-world entities. A major focus lies on the efficient derivation of coherent links. For each of the contributions, we provide a wide range of experiments on various text corpora as well as different sources of UGC. The evaluation shows the added value that the usage of these sources provides and confirms the appropriateness of leveraging user-generated content to serve different information needs. N2 - Die steigende Zahl an Dokumenten, welche in den letzten Jahren im Web sowie in geschlossenen Systemen aus dem privaten oder geschäftlichen Umfeld erstellt wurden, führte zu einem erheblichen Zuwachs an wertvollen Informationen über verschiedenste Themen, Ereignisse, Organisationen und Personen. Die meisten Informationen liegen lediglich in unstrukturierter, textueller Form vor. Das Forschungsgebiet des "Text Mining" befasst sich mit dem schwierigen Problem, hochwertige Informationen in strukturierter Form aus Texten zu gewinnen. Diese Informationen können dazu eingesetzt werden, Nutzern dabei zu helfen, ihren Informationsbedarf zu stillen. In dieser Arbeit nutzen wir Wissen, welches in nutzergenerierten Inhalten verborgen ist und aus unterschiedlichsten sozialen Medien stammt, um Text Mining Ergebnisse zu verbessern. Soziale Medien bieten eine Fülle an Informationen mit verschiedenen Schwerpunkten. Eine wesentliche Funktion solcher Medien ist es, den Nutzern zu ermöglichen, Inhalte mit ihrer Interessensgruppe zu teilen. Somit sind die ausgetauschten Daten in diesen Diensten häufig auf die Interessen der Nutzerbasis ausgerichtet. Die Popularität sozialer Medien wächst stetig und führt dazu, dass immer mehr inhärentes Wissen verfügbar wird. Dieses Wissen kann unter anderem für drei verschiedene Aufgabenstellungen genutzt werden. Zunächst zeigen wir, dass Informationen aus Wikipedia hilfreich sind, um Ergebnisse von Personensuchen im Web nach den in ihnen diskutierten Personen aufzuteilen. Dazu führen wir zwei Modelle zur Gruppierung der Ergebnisse und verschiedene Methoden zum Umgang mit fehlenden Wikipedia Einträgen ein, und zeigen, dass die entwickelten Ansätze traditionelle Methoden zur Gruppierung von Suchergebnissen übertreffen. Des Weiteren diskutieren wir, wie die Klassifizierung von Texten auf Basis von "Folksonomien" Nutzern dabei helfen kann, neue Informationen zu identifizieren, die ihren Interessen entsprechen. Wir konzentrieren uns insbesondere auf temporäre Änderungen in den nutzergenerierten Inhalten, um zu zeigen, wie stark ihr Einfluss auf die Qualität verschiedener "Tag"-Empfehlungsmethoden ist. Zu guter Letzt führen wir einen Algorithmus ein, der es ermöglicht, Nennungen von Echtweltinstanzen in Texten zu disambiguieren und mit ihren Repräsentationen in einer Wissensdatenbank zu verknüpfen. Das Hauptaugenmerk liegt dabei auf der effizienten Erkennung von kohärenten Verknüpfungen. Wir stellen für jeden Teil der Arbeit eine große Vielfalt an Experimenten auf diversen Textkorpora und unterschiedlichen Quellen von nutzergenerierten Inhalten an. Damit heben wir das Potential hervor, das die Nutzung jener Quellen bietet, um die unterschiedlichen Informationsbedürfnisse abzudecken. T2 - Mehrwert für Texte mittels nutzergenerierter Inhalte KW - nutzergenerierte Inhalte KW - text mining KW - Klassifikation KW - Clusteranalyse KW - Entitätsverknüpfung KW - user-generated content KW - text mining KW - classification KW - clustering KW - entity linking Y1 - 2018 ER - TY - GEN A1 - Matthies, Christoph T1 - Agile process improvement in retrospectives T2 - 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) N2 - Working in iterations and repeatedly improving team workflows based on collected feedback is fundamental to agile software development processes. Scrum, the most popular agile method, provides dedicated retrospective meetings to reflect on the last development iteration and to decide on process improvement actions. However, agile methods do not prescribe how these improvement actions should be identified, managed or tracked in detail. The approaches to detect and remove problems in software development processes are therefore often based on intuition and prior experiences and perceptions of team members. Previous research in this area has focused on approaches to elicit a team's improvement opportunities as well as measurements regarding the work performed in an iteration, e.g. Scrum burn-down charts. Little research deals with the quality and nature of identified problems or how progress towards removing issues is measured. In this research, we investigate how agile development teams in the professional software industry organize their feedback and process improvement approaches. In particular, we focus on the structure and content of improvement and reflection meetings, i.e. retrospectives, and their outcomes. Researching how the vital mechanism of process improvement is implemented in practice in modern software development leads to a more complete picture of agile process improvement. KW - Agile KW - Scrum KW - software process improvement KW - retrospective Y1 - 2019 SN - 978-1-7281-1764-5 SN - 978-1-7281-1765-2 U6 - https://doi.org/10.1109/ICSE-Companion.2019.00063 SN - 2574-1934 SN - 2574-1926 SP - 150 EP - 152 PB - IEEE CY - New York ER - TY - JOUR A1 - Haugsbakken, Halvdan A1 - Hagelia, Marianne ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - An asynchronous cooperative leaning design in a Small Private Online Course (SPOC) JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - This short paper sets out to propose a novel and interesting learning design that facilitates for cooperative learning in which students do not conduct traditional group work in an asynchronous online education setting. This learning design will be explored in a Small Private Online Course (SPOC) among teachers and school managers at a teacher education. Such an approach can be made possible by applying specific criteria commonly used to define collaborative learning. Collaboration can be defined, among other things, as a structured way of working among students that includes elements of co-laboring. The cooperative learning design involves adapting various traditional collaborative learning approaches for use in an online learning environment. A critical component of this learning design is that students work on a self-defined case project related to their professional practices. Through an iterative process, students will receive ongoing feedback and formative assessments from instructors and follow students at specific points, meaning that co-constructing of knowledge and learning takes place as the SPOC progresses. This learning design can contribute to better learning experiences and outcomes for students, and be a valuable contribution to current research discussions on learning design in Massive Open Online Courses (MOOCs). KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-622107 SP - 67 EP - 76 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Aranda, Juan A1 - Schölzel, Mario A1 - Mendez, Diego A1 - Carrillo, Henry T1 - An energy consumption model for multiModal wireless sensor networks based on wake-up radio receivers T2 - 2018 IEEE Colombian Conference on Communications and Computing (COLCOM) N2 - Energy consumption is a major concern in Wireless Sensor Networks. A significant waste of energy occurs due to the idle listening and overhearing problems, which are typically avoided by turning off the radio, while no transmission is ongoing. The classical approach for allowing the reception of messages in such situations is to use a low-duty-cycle protocol, and to turn on the radio periodically, which reduces the idle listening problem, but requires timers and usually unnecessary wakeups. A better solution is to turn on the radio only on demand by using a Wake-up Radio Receiver (WuRx). In this paper, an energy model is presented to estimate the energy saving in various multi-hop network topologies under several use cases, when a WuRx is used instead of a classical low-duty-cycling protocol. The presented model also allows for estimating the benefit of various WuRx properties like using addressing or not. KW - Energy efficiency KW - multimodal wireless sensor network KW - low-duty-cycling KW - wake-up radio Y1 - 2018 SN - 978-1-5386-6820-7 U6 - https://doi.org/10.1109/ColComCon.2018.8466728 PB - IEEE CY - New York ER - TY - JOUR A1 - Concia, Francesca A1 - Distler, Petr A1 - Law, Gareth A1 - Macerata, Elena A1 - Mariani, Mario A1 - Mossini, Eros A1 - Negrin, Maddalena A1 - Štrok, Marko ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - An experience in developing models to use MOOCs in teaching and to advocate OERs JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - Loss of expertise in the fields of Nuclear- and Radio-Chemistry (NRC) is problematic at a scientific and social level. This has been addressed by developing a MOOC, in order to let students in scientific matters discover all the benefits of NRC to society and improving their awareness of this discipline. The MOOC “Essential Radiochemistry for Society” includes current societal challenges related to health, clean and sustainable energy for safety and quality of food and agriculture. NRC teachers belonging to CINCH network were invited to use the MOOC in their teaching, according to various usage models: on the basis of these different experiences, some usage patterns were designed, describing context characteristics (number and age of students, course), activities’ scheduling and organization, results and students’ feedback, with the aim of encouraging the use of MOOCs in university teaching, as an opportunity for both lecturers and students. These models were the basis of a “toolkit for teachers”. By experiencing digital teaching resources created by different lecturers, CINCH teachers took a first meaningful step towards understanding the worth of Open Educational Resources (OER) and the importance of their creation, adoption and sharing for knowledge progress. In this paper, the entire path from MOOC concept to MOOC different usage models, to awareness-raising regarding OER is traced in conceptual stages. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624609 SP - 239 EP - 254 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - BOOK A1 - Baltzer, Wanda A1 - Hradilak, Theresa A1 - Pfennigschmidt, Lara A1 - Prestin, Luc Maurice A1 - Spranger, Moritz A1 - Stadlinger, Simon A1 - Wendt, Leo A1 - Lincke, Jens A1 - Rein, Patrick A1 - Church, Luke A1 - Hirschfeld, Robert T1 - An individual-centered approach to visualize people’s opinions and demographic information N2 - The noble way to substantiate decisions that affect many people is to ask these people for their opinions. For governments that run whole countries, this means asking all citizens for their views to consider their situations and needs. Organizations such as Africa's Voices Foundation, who want to facilitate communication between decision-makers and citizens of a country, have difficulty mediating between these groups. To enable understanding, statements need to be summarized and visualized. Accomplishing these goals in a way that does justice to the citizens' voices and situations proves challenging. Standard charts do not help this cause as they fail to create empathy for the people behind their graphical abstractions. Furthermore, these charts do not create trust in the data they are representing as there is no way to see or navigate back to the underlying code and the original data. To fulfill these functions, visualizations would highly benefit from interactions to explore the displayed data, which standard charts often only limitedly provide. To help improve the understanding of people's voices, we developed and categorized 80 ideas for new visualizations, new interactions, and better connections between different charts, which we present in this report. From those ideas, we implemented 10 prototypes and two systems that integrate different visualizations. We show that this integration allows consistent appearance and behavior of visualizations. The visualizations all share the same main concept: representing each individual with a single dot. To realize this idea, we discuss technologies that efficiently allow the rendering of a large number of these dots. With these visualizations, direct interactions with representations of individuals are achievable by clicking on them or by dragging a selection around them. This direct interaction is only possible with a bidirectional connection from the visualization to the data it displays. We discuss different strategies for bidirectional mappings and the trade-offs involved. Having unified behavior across visualizations enhances exploration. For our prototypes, that includes grouping, filtering, highlighting, and coloring of dots. Our prototyping work was enabled by the development environment Lively4. We explain which parts of Lively4 facilitated our prototyping process. Finally, we evaluate our approach to domain problems and our developed visualization concepts. Our work provides inspiration and a starting point for visualization development in this domain. Our visualizations can improve communication between citizens and their government and motivate empathetic decisions. Our approach, combining low-level entities to create visualizations, provides value to an explorative and empathetic workflow. We show that the design space for visualizing this kind of data has a lot of potential and that it is possible to combine qualitative and quantitative approaches to data analysis. N2 - Der noble Weg, Entscheidungen, die viele Menschen betreffen, zu begründen, besteht darin, diese Menschen nach ihrer Meinung zu fragen. Für Regierungen, die ganze Länder führen, bedeutet dies, alle Bürger nach ihrer Meinung zu fragen, um ihre Situationen und Bedürfnisse zu berücksichtigen. Organisationen wie die Africa's Voices Foundation, die die Kommunikation zwischen Entscheidungsträgern und Bürgern eines Landes erleichtern wollen, haben Schwierigkeiten, zwischen diesen Gruppen zu vermitteln. Um Verständnis zu ermöglichen, müssen die Aussagen zusammengefasst und visualisiert werden. Diese Ziele auf eine Weise zu erreichen, die den Stimmen und Situationen der Bürgerinnen und Bürger gerecht wird, erweist sich als Herausforderung. Standardgrafiken helfen dabei nicht weiter, da es ihnen nicht gelingt, Empathie für die Menschen hinter ihren grafischen Abstraktionen zu schaffen. Darüber hinaus schaffen diese Diagramme kein Vertrauen in die Daten, die sie darstellen, da es keine Möglichkeit gibt, den verwendeten Code und die Originaldaten zu sehen oder zu ihnen zurück zu navigieren. Um diese Funktionen zu erfüllen, würden Visualisierungen sehr von Interaktionen zur Erkundung der angezeigten Daten profitieren, die Standardgrafiken oft nur begrenzt bieten. Um das Verständnis der Stimmen der Menschen zu verbessern, haben wir 80 Ideen für neue Visualisierungen, neue Interaktionen und bessere Verbindungen zwischen verschiedenen Diagrammen entwickelt und kategorisiert, die wir in diesem Bericht vorstellen. Aus diesen Ideen haben wir 10 Prototypen und zwei Systeme implementiert, die verschiedene Visualisierungen integrieren. Wir zeigen, dass diese Integration ein einheitliches Erscheinungsbild und Verhalten der Visualisierungen ermöglicht. Die Visualisierungen haben alle das gleiche Grundkonzept: Jedes Individuum wird durch einen einzigen Punkt dargestellt. Um diese Idee zu verwirklichen, diskutieren wir Technologien, die die effiziente Darstellung einer großen Anzahl dieser Punkte ermöglichen. Mit diesen Visualisierungen sind direkte Interaktionen mit Darstellungen von Individuen möglich, indem man auf sie klickt oder eine Auswahl um sie herumzieht. Diese direkte Interaktion ist nur mit einer bidirektionalen Verbindung von der Visualisierung zu den angezeigten Daten möglich. Wir diskutieren verschiedene Strategien für bidirektionale Mappings und die damit verbundenen Kompromisse. Ein einheitliches Verhalten über Visualisierungen hinweg verbessert die Exploration. Für unsere Prototypen umfasst dies Gruppierung, Filterung, Hervorhebung und Einfärbung von Punkten. Unsere Arbeit an den Prototypen wurde durch die Entwicklungsumgebung Lively4 ermöglicht. Wir erklären, welche Teile von Lively4 unseren Prototyping-Prozess erleichtert haben. Schließlich bewerten wir unsere Herangehensweise an Domänenprobleme und die von uns entwickelten Visualisierungskonzepte. Unsere Arbeit liefert Inspiration und einen Ausgangspunkt für die Entwicklung von Visualisierungen in diesem Bereich. Unsere Visualisierungen können die Kommunikation zwischen Bürgern und ihrer Regierung verbessern und einfühlsame Entscheidungen motivieren. Unser Ansatz, bei dem wir niedrigstufige Entitäten zur Erstellung von Visualisierungen kombinieren, bietet einen wertvollen Ansatz für einen explorativen und einfühlsamen Arbeitsablauf. Wir zeigen, dass der Designraum für die Visualisierung dieser Art von Daten ein großes Potenzial hat und dass es möglich ist, qualitative und quantitative Ansätze zur Datenanalyse zu kombinieren. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 136 KW - data visualization KW - demographic information KW - visualization concept exploration KW - web-based development environment KW - Datenvisualisierung KW - demografische Informationen KW - Visualisierungskonzept-Exploration KW - web-basierte Entwicklungsumgebung Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-491457 SN - 978-3-86956-504-0 SN - 1613-5652 SN - 2191-1665 IS - 136 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Patalas-Maliszewska, Justyna A1 - Krebs, Irene T1 - An Information System Supporting the Eliciting of Expert Knowledge for Successful IT Projects T2 - Information and Software Technologies, ICIST 2018 N2 - In order to guarantee the success of an IT project, it is necessary for a company to possess expert knowledge. The difficulty arises when experts no longer work for the company and it then becomes necessary to use their knowledge, in order to realise an IT project. In this paper, the ExKnowIT information system which supports the eliciting of expert knowledge for successful IT projects, is presented and consists of the following modules: (1) the identification of experts for successful IT projects, (2) the eliciting of expert knowledge on completed IT projects, (3) the expert knowledge base on completed IT projects, (4) the Group Method for Data Handling (GMDH) algorithm, (5) new knowledge in support of decisions regarding the selection of a manager for a new IT project. The added value of our system is that these three approaches, namely, the elicitation of expert knowledge, the success of an IT project and the discovery of new knowledge, gleaned from the expert knowledge base, otherwise known as the decision model, complement each other. KW - Expert knowledge KW - IT project KW - Information system KW - GMDH Y1 - 2018 SN - 978-3-319-99972-2 SN - 978-3-319-99971-5 U6 - https://doi.org/10.1007/978-3-319-99972-2_1 SN - 1865-0929 SN - 1865-0937 VL - 920 SP - 3 EP - 13 PB - Springer CY - Berlin ER - TY - JOUR A1 - Kunft, Andreas A1 - Katsifodimos, Asterios A1 - Schelter, Sebastian A1 - Bress, Sebastian A1 - Rabl, Tilmann A1 - Markl, Volker T1 - An Intermediate Representation for Optimizing Machine Learning Pipelines JF - Proceedings of the VLDB Endowment N2 - Machine learning (ML) pipelines for model training and validation typically include preprocessing, such as data cleaning and feature engineering, prior to training an ML model. Preprocessing combines relational algebra and user-defined functions (UDFs), while model training uses iterations and linear algebra. Current systems are tailored to either of the two. As a consequence, preprocessing and ML steps are optimized in isolation. To enable holistic optimization of ML training pipelines, we present Lara, a declarative domain-specific language for collections and matrices. Lara's inter-mediate representation (IR) reflects on the complete program, i.e., UDFs, control flow, and both data types. Two views on the IR enable diverse optimizations. Monads enable operator pushdown and fusion across type and loop boundaries. Combinators provide the semantics of domain-specific operators and optimize data access and cross-validation of ML algorithms. Our experiments on preprocessing pipelines and selected ML algorithms show the effects of our proposed optimizations on dense and sparse data, which achieve speedups of up to an order of magnitude. Y1 - 2019 U6 - https://doi.org/10.14778/3342263.3342633 SN - 2150-8097 VL - 12 IS - 11 SP - 1553 EP - 1567 PB - Association for Computing Machinery CY - New York ER - TY - THES A1 - Wolf, Johannes T1 - Analysis and visualization of transport infrastructure based on large-scale geospatial mobile mapping data T1 - Analyse und Visualisierung von Verkehrsinfrastruktur basierend auf großen Mobile-Mapping-Datensätzen N2 - 3D point clouds are a universal and discrete digital representation of three-dimensional objects and environments. For geospatial applications, 3D point clouds have become a fundamental type of raw data acquired and generated using various methods and techniques. In particular, 3D point clouds serve as raw data for creating digital twins of the built environment. This thesis concentrates on the research and development of concepts, methods, and techniques for preprocessing, semantically enriching, analyzing, and visualizing 3D point clouds for applications around transport infrastructure. It introduces a collection of preprocessing techniques that aim to harmonize raw 3D point cloud data, such as point density reduction and scan profile detection. Metrics such as, e.g., local density, verticality, and planarity are calculated for later use. One of the key contributions tackles the problem of analyzing and deriving semantic information in 3D point clouds. Three different approaches are investigated: a geometric analysis, a machine learning approach operating on synthetically generated 2D images, and a machine learning approach operating on 3D point clouds without intermediate representation. In the first application case, 2D image classification is applied and evaluated for mobile mapping data focusing on road networks to derive road marking vector data. The second application case investigates how 3D point clouds can be merged with ground-penetrating radar data for a combined visualization and to automatically identify atypical areas in the data. For example, the approach detects pavement regions with developing potholes. The third application case explores the combination of a 3D environment based on 3D point clouds with panoramic imagery to improve visual representation and the detection of 3D objects such as traffic signs. The presented methods were implemented and tested based on software frameworks for 3D point clouds and 3D visualization. In particular, modules for metric computation, classification procedures, and visualization techniques were integrated into a modular pipeline-based C++ research framework for geospatial data processing, extended by Python machine learning scripts. All visualization and analysis techniques scale to large real-world datasets such as road networks of entire cities or railroad networks. The thesis shows that some use cases allow taking advantage of established image vision methods to analyze images rendered from mobile mapping data efficiently. The two presented semantic classification methods working directly on 3D point clouds are use case independent and show similar overall accuracy when compared to each other. While the geometry-based method requires less computation time, the machine learning-based method supports arbitrary semantic classes but requires training the network with ground truth data. Both methods can be used in combination to gradually build this ground truth with manual corrections via a respective annotation tool. This thesis contributes results for IT system engineering of applications, systems, and services that require spatial digital twins of transport infrastructure such as road networks and railroad networks based on 3D point clouds as raw data. It demonstrates the feasibility of fully automated data flows that map captured 3D point clouds to semantically classified models. This provides a key component for seamlessly integrated spatial digital twins in IT solutions that require up-to-date, object-based, and semantically enriched information about the built environment. N2 - 3D-Punktwolken sind eine universelle und diskrete digitale Darstellung von dreidimensionalen Objekten und Umgebungen. Für raumbezogene Anwendungen sind 3D-Punktwolken zu einer grundlegenden Form von Rohdaten geworden, die mit verschiedenen Methoden und Techniken erfasst und erzeugt werden. Insbesondere dienen 3D-Punktwolken als Rohdaten für die Erstellung digitaler Zwillinge der bebauten Umwelt. Diese Arbeit konzentriert sich auf die Erforschung und Entwicklung von Konzepten, Methoden und Techniken zur Vorverarbeitung, semantischen Anreicherung, Analyse und Visualisierung von 3D-Punktwolken für Anwendungen im Bereich der Verkehrsinfrastruktur. Es wird eine Sammlung von Vorverarbeitungstechniken vorgestellt, die auf die Harmonisierung von 3D-Punktwolken-Rohdaten abzielen, so z.B. die Reduzierung der Punktdichte und die Erkennung von Scanprofilen. Metriken wie bspw. die lokale Dichte, Vertikalität und Planarität werden zur späteren Verwendung berechnet. Einer der Hauptbeiträge befasst sich mit dem Problem der Analyse und Ableitung semantischer Informationen in 3D-Punktwolken. Es werden drei verschiedene Ansätze untersucht: Eine geometrische Analyse sowie zwei maschinelle Lernansätze, die auf synthetisch erzeugten 2D-Bildern, bzw. auf 3D-Punktwolken ohne Zwischenrepräsentation arbeiten. Im ersten Anwendungsfall wird die 2D-Bildklassifikation für Mobile-Mapping-Daten mit Fokus auf Straßennetze angewendet und evaluiert, um Vektordaten für Straßenmarkierungen abzuleiten. Im zweiten Anwendungsfall wird untersucht, wie 3D-Punktwolken mit Bodenradardaten für eine kombinierte Visualisierung und automatische Identifikation atypischer Bereiche in den Daten zusammengeführt werden können. Der Ansatz erkennt zum Beispiel Fahrbahnbereiche mit entstehenden Schlaglöchern. Der dritte Anwendungsfall untersucht die Kombination einer 3D-Umgebung auf Basis von 3D-Punktwolken mit Panoramabildern, um die visuelle Darstellung und die Erkennung von 3D-Objekten wie Verkehrszeichen zu verbessern. Die vorgestellten Methoden wurden auf Basis von Software-Frameworks für 3D-Punktwolken und 3D-Visualisierung implementiert und getestet. Insbesondere wurden Module für Metrikberechnungen, Klassifikationsverfahren und Visualisierungstechniken in ein modulares, pipelinebasiertes C++-Forschungsframework für die Geodatenverarbeitung integriert, das durch Python-Skripte für maschinelles Lernen erweitert wurde. Alle Visualisierungs- und Analysetechniken skalieren auf große reale Datensätze wie Straßennetze ganzer Städte oder Eisenbahnnetze. Die Arbeit zeigt, dass es in einigen Anwendungsfällen möglich ist, die Vorteile etablierter Bildverarbeitungsmethoden zu nutzen, um aus Mobile-Mapping-Daten gerenderte Bilder effizient zu analysieren. Die beiden vorgestellten semantischen Klassifikationsverfahren, die direkt auf 3D-Punktwolken arbeiten, sind anwendungsfallunabhängig und zeigen im Vergleich zueinander eine ähnliche Gesamtgenauigkeit. Während die geometriebasierte Methode weniger Rechenzeit benötigt, unterstützt die auf maschinellem Lernen basierende Methode beliebige semantische Klassen, erfordert aber das Trainieren des Netzwerks mit Ground-Truth-Daten. Beide Methoden können in Kombination verwendet werden, um diese Ground Truth mit manuellen Korrekturen über ein entsprechendes Annotationstool schrittweise aufzubauen. Diese Arbeit liefert Ergebnisse für das IT-System-Engineering von Anwendungen, Systemen und Diensten, die räumliche digitale Zwillinge von Verkehrsinfrastruktur wie Straßen- und Schienennetzen auf der Basis von 3D-Punktwolken als Rohdaten benötigen. Sie demonstriert die Machbarkeit von vollautomatisierten Datenflüssen, die erfasste 3D-Punktwolken auf semantisch klassifizierte Modelle abbilden. Dies stellt eine Schlüsselkomponente für nahtlos integrierte räumliche digitale Zwillinge in IT-Lösungen dar, die aktuelle, objektbasierte und semantisch angereicherte Informationen über die bebaute Umwelt benötigen. KW - 3D point cloud KW - geospatial data KW - mobile mapping KW - semantic classification KW - 3D visualization KW - 3D-Punktwolke KW - räumliche Geodaten KW - Mobile Mapping KW - semantische Klassifizierung KW - 3D-Visualisierung Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-536129 ER - TY - THES A1 - Ussath, Martin Georg T1 - Analytical approaches for advanced attacks Y1 - 2017 ER - TY - JOUR A1 - Buschmann, Stefan A1 - Trapp, Matthias A1 - Döllner, Jürgen Roland Friedrich T1 - Animated visualization of spatial-temporal trajectory data for air-traffic analysis JF - The Visual Computer N2 - With increasing numbers of flights worldwide and a continuing rise in airport traffic, air-traffic management is faced with a number of challenges. These include monitoring, reporting, planning, and problem analysis of past and current air traffic, e.g., to identify hotspots, minimize delays, or to optimize sector assignments to air-traffic controllers. To cope with these challenges, cyber worlds can be used for interactive visual analysis and analytical reasoning based on aircraft trajectory data. However, with growing data size and complexity, visualization requires high computational efficiency to process that data within real-time constraints. This paper presents a technique for real-time animated visualization of massive trajectory data. It enables (1) interactive spatio-temporal filtering, (2) generic mapping of trajectory attributes to geometric representations and appearance, and (3) real-time rendering within 3D virtual environments such as virtual 3D airport or 3D city models. Different visualization metaphors can be efficiently built upon this technique such as temporal focus+context, density maps, or overview+detail methods. As a general-purpose visualization technique, it can be applied to general 3D and 3+1D trajectory data, e.g., traffic movement data, geo-referenced networks, or spatio-temporal data, and it supports related visual analytics and data mining tasks within cyber worlds. KW - Spatio-temporal visualization KW - Trajectory visualization KW - 3D visualization KW - Visual analytics KW - Real-time rendering Y1 - 2016 U6 - https://doi.org/10.1007/s00371-015-1185-9 SN - 0178-2789 SN - 1432-2315 VL - 32 SP - 371 EP - 381 PB - Springer CY - New York ER - TY - GEN A1 - Bin Tareaf, Raad A1 - Berger, Philipp A1 - Hennig, Patrick A1 - Meinel, Christoph T1 - ASEDS BT - Towards automatic social emotion detection system using facebook reactions T2 - IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)) N2 - The Massive adoption of social media has provided new ways for individuals to express their opinion and emotion online. In 2016, Facebook introduced a new reactions feature that allows users to express their psychological emotions regarding published contents using so-called Facebook reactions. In this paper, a framework for predicting the distribution of Facebook post reactions is presented. For this purpose, we collected an enormous amount of Facebook posts associated with their reactions labels using the proposed scalable Facebook crawler. The training process utilizes 3 million labeled posts for more than 64,000 unique Facebook pages from diverse categories. The evaluation on standard benchmarks using the proposed features shows promising results compared to previous research. The final model is able to predict the reaction distribution on Facebook posts with a recall score of 0.90 for "Joy" emotion. KW - Emotion Mining KW - Psychological Emotions KW - Machine Learning KW - Social Media Analysis KW - Natural Language Processing Y1 - 2018 SN - 978-1-5386-6614-2 U6 - https://doi.org/10.1109/HPCC/SmartCity/DSS.2018.00143 SP - 860 EP - 866 PB - IEEE CY - New York ER - TY - GEN A1 - Ullrich, Andre A1 - Enke, Judith A1 - Teichmann, Malte A1 - Kress, Antonio A1 - Gronau, Norbert T1 - Audit - and then what? BT - a roadmap for digitization of learning factories T2 - Procedia Manufacturing N2 - Current trends such as digital transformation, Internet of Things, or Industry 4.0 are challenging the majority of learning factories. Regardless of whether a conventional learning factory, a model factory, or a digital learning factory, traditional approaches such as the monotonous execution of specific instructions don‘t suffice the learner’s needs, market requirements as well as especially current technological developments. Contemporary teaching environments need a clear strategy, a road to follow for being able to successfully cope with the changes and develop towards digitized learning factories. This demand driven necessity of transformation leads to another obstacle: Assessing the status quo and developing and implementing adequate action plans. Within this paper, details of a maturity-based audit of the hybrid learning factory in the Research and Application Centre Industry 4.0 and a thereof derived roadmap for the digitization of a learning factory are presented. KW - Audit KW - Digitization KW - Learning Factory KW - Roadmap Y1 - 2019 U6 - https://doi.org/10.1016/j.promfg.2019.03.025 SN - 2351-9789 VL - 31 SP - 162 EP - 168 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schlosser, Rainer A1 - Walther, Carsten A1 - Boissier, Martin A1 - Uflacker, Matthias T1 - Automated repricing and ordering strategies in competitive markets JF - AI communications : AICOM ; the European journal on artificial intelligence N2 - Merchants on modern e-commerce platforms face a highly competitive environment. They compete against each other using automated dynamic pricing and ordering strategies. Successfully managing both inventory levels as well as offer prices is a challenging task as (i) demand is uncertain, (ii) competitors strategically interact, and (iii) optimized pricing and ordering decisions are mutually dependent. We show how to derive optimized data-driven pricing and ordering strategies which are based on demand learning techniques and efficient dynamic optimization models. We verify the superior performance of our self-adaptive strategies by comparing them to different rule-based as well as data-driven strategies in duopoly and oligopoly settings. Further, to study and to optimize joint dynamic ordering and pricing strategies on online marketplaces, we built an interactive simulation platform. To be both flexible and scalable, the platform has a microservice-based architecture and allows handling dozens of competing merchants and streams of consumers with configurable characteristics. KW - Dynamic pricing KW - inventory management KW - demand learning KW - oligopoly competition KW - e-commerce Y1 - 2019 U6 - https://doi.org/10.3233/AIC-180603 SN - 0921-7126 SN - 1875-8452 VL - 32 IS - 1 SP - 15 EP - 29 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Dyck, Johannes A1 - Giese, Holger A1 - Lambers, Leen T1 - Automatic verification of behavior preservation at the transformation level for relational model transformation JF - Software and systems modeling N2 - The correctness of model transformations is a crucial element for model-driven engineering of high-quality software. In particular, behavior preservation is an important correctness property avoiding the introduction of semantic errors during the model-driven engineering process. Behavior preservation verification techniques show some kind of behavioral equivalence or refinement between source and target model of the transformation. Automatic tool support is available for verifying behavior preservation at the instance level, i.e., for a given source and target model specified by the model transformation. However, until now there is no sound and automatic verification approach available at the transformation level, i.e., for all source and target models. In this article, we extend our results presented in earlier work (Giese and Lambers, in: Ehrig et al (eds) Graph transformations, Springer, Berlin, 2012) and outline a new transformation-level approach for the sound and automatic verification of behavior preservation captured by bisimulation resp.simulation for outplace model transformations specified by triple graph grammars and semantic definitions given by graph transformation rules. In particular, we first show how behavior preservation can be modeled in a symbolic manner at the transformation level and then describe that transformation-level verification of behavior preservation can be reduced to invariant checking of suitable conditions for graph transformations. We demonstrate that the resulting checking problem can be addressed by our own invariant checker for an example of a transformation between sequence charts and communicating automata. KW - Relational model transformation KW - Formal verification of behavior preservation KW - Behavioral equivalence and refinement KW - Bisimulation and simulation KW - Graph transformation KW - Triple graph grammars KW - Invariant checking Y1 - 2018 U6 - https://doi.org/10.1007/s10270-018-00706-9 SN - 1619-1366 SN - 1619-1374 VL - 18 IS - 5 SP - 2937 EP - 2972 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Gawron, Marian A1 - Cheng, Feng A1 - Meinel, Christoph T1 - Automatic vulnerability classification using machine learning T2 - Risks and Security of Internet and Systems N2 - The classification of vulnerabilities is a fundamental step to derive formal attributes that allow a deeper analysis. Therefore, it is required that this classification has to be performed timely and accurate. Since the current situation demands a manual interaction in the classification process, the timely processing becomes a serious issue. Thus, we propose an automated alternative to the manual classification, because the amount of identified vulnerabilities per day cannot be processed manually anymore. We implemented two different approaches that are able to automatically classify vulnerabilities based on the vulnerability description. We evaluated our approaches, which use Neural Networks and the Naive Bayes methods respectively, on the base of publicly known vulnerabilities. KW - Vulnerability analysis KW - Security analytics KW - Data mining Machine learning KW - Neural Networks Y1 - 2018 SN - 978-3-319-76687-4 SN - 978-3-319-76686-7 U6 - https://doi.org/10.1007/978-3-319-76687-4_1 SN - 0302-9743 SN - 1611-3349 SP - 3 EP - 17 PB - Springer CY - Cham ER - TY - JOUR A1 - Pufahl, Luise A1 - Weske, Mathias T1 - Batch activity: enhancing business process modeling and enactment with batch processing JF - Computing N2 - Organizations strive for efficiency in their business processes by process improvement and automation. Business process management (BPM) supports these efforts by capturing business processes in process models serving as blueprint for a number of process instances. In BPM, process instances are typically considered running independently of each other. However, batch processing-the collectively execution of several instances at specific process activities-is a common phenomenon in operational processes to reduce cost or time. Currently, batch processing is organized manually or hard-coded in software. For allowing stakeholders to explicitly represent their batch configurations in process models and their automatic execution, this paper provides a concept for batch activities and describes the corresponding execution semantics. The batch activity concept is evaluated in a two-step approach: a prototypical implementation in an existing BPM System proves its feasibility. Additionally, batch activities are applied to different use cases in a simulated environment. Its application implies cost-savings when a suitable batch configuration is selected. The batch activity concept contributes to practice by allowing the specification of batch work in process models and their automatic execution, and to research by extending the existing process modeling concepts. KW - Batch activity KW - Batch processing KW - Business process models KW - Process Enactment KW - Colored Petri Net Y1 - 2019 U6 - https://doi.org/10.1007/s00607-019-00717-4 SN - 0010-485X SN - 1436-5057 VL - 101 IS - 12 SP - 1909 EP - 1933 PB - Springer CY - Wien ER - TY - GEN A1 - Repke, Tim A1 - Krestel, Ralf A1 - Edding, Jakob A1 - Hartmann, Moritz A1 - Hering, Jonas A1 - Kipping, Dennis A1 - Schmidt, Hendrik A1 - Scordialo, Nico A1 - Zenner, Alexander T1 - Beacon in the Dark BT - a system for interactive exploration of large email Corpora T2 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management N2 - The large amount of heterogeneous data in these email corpora renders experts' investigations by hand infeasible. Auditors or journalists, e.g., who are looking for irregular or inappropriate content or suspicious patterns, are in desperate need for computer-aided exploration tools to support their investigations. We present our Beacon system for the exploration of such corpora at different levels of detail. A distributed processing pipeline combines text mining methods and social network analysis to augment the already semi-structured nature of emails. The user interface ties into the resulting cleaned and enriched dataset. For the interface design we identify three objectives expert users have: gain an initial overview of the data to identify leads to investigate, understand the context of the information at hand, and have meaningful filters to iteratively focus onto a subset of emails. To this end we make use of interactive visualisations based on rearranged and aggregated extracted information to reveal salient patterns. Y1 - 2018 SN - 978-1-4503-6014-2 U6 - https://doi.org/10.1145/3269206.3269231 SP - 1871 EP - 1874 PB - Association for Computing Machinery CY - New York ER - TY - THES A1 - Meinig, Michael T1 - Bedrohungsanalyse für militärische Informationstechnik T1 - Threat analysis for military information technology N2 - Risiken für Cyberressourcen können durch unbeabsichtigte oder absichtliche Bedrohungen entstehen. Dazu gehören Insider-Bedrohungen von unzufriedenen oder nachlässigen Mitarbeitern und Partnern, eskalierende und aufkommende Bedrohungen aus aller Welt, die stetige Weiterentwicklung der Angriffstechnologien und die Entstehung neuer und zerstörerischer Angriffe. Informationstechnik spielt mittlerweile in allen Bereichen des Lebens eine entscheidende Rolle, u. a. auch im Bereich des Militärs. Ein ineffektiver Schutz von Cyberressourcen kann hier Sicherheitsvorfälle und Cyberattacken erleichtern, welche die kritischen Vorgänge stören, zu unangemessenem Zugriff, Offenlegung, Änderung oder Zerstörung sensibler Informationen führen und somit die nationale Sicherheit, das wirtschaftliche Wohlergehen sowie die öffentliche Gesundheit und Sicherheit gefährden. Oftmals ist allerdings nicht klar, welche Bedrohungen konkret vorhanden sind und welche der kritischen Systemressourcen besonders gefährdet ist. In dieser Dissertation werden verschiedene Analyseverfahren für Bedrohungen in militärischer Informationstechnik vorgeschlagen und in realen Umgebungen getestet. Dies bezieht sich auf Infrastrukturen, IT-Systeme, Netze und Anwendungen, welche Verschlusssachen (VS)/Staatsgeheimnisse verarbeiten, wie zum Beispiel bei militärischen oder Regierungsorganisationen. Die Besonderheit an diesen Organisationen ist das Konzept der Informationsräume, in denen verschiedene Datenelemente, wie z. B. Papierdokumente und Computerdateien, entsprechend ihrer Sicherheitsempfindlichkeit eingestuft werden, z. B. „STRENG GEHEIM“, „GEHEIM“, „VS-VERTRAULICH“, „VS-NUR-FÜR-DEN-DIENSTGEBRAUCH“ oder „OFFEN“. Die Besonderheit dieser Arbeit ist der Zugang zu eingestuften Informationen aus verschiedenen Informationsräumen und der Prozess der Freigabe dieser. Jede in der Arbeit entstandene Veröffentlichung wurde mit Angehörigen in der Organisation besprochen, gegengelesen und freigegeben, so dass keine eingestuften Informationen an die Öffentlichkeit gelangen. Die Dissertation beschreibt zunächst Bedrohungsklassifikationsschemen und Angreiferstrategien, um daraus ein ganzheitliches, strategiebasiertes Bedrohungsmodell für Organisationen abzuleiten. Im weiteren Verlauf wird die Erstellung und Analyse eines Sicherheitsdatenflussdiagramms definiert, welches genutzt wird, um in eingestuften Informationsräumen operationelle Netzknoten zu identifizieren, die aufgrund der Bedrohungen besonders gefährdet sind. Die spezielle, neuartige Darstellung ermöglicht es, erlaubte und verbotene Informationsflüsse innerhalb und zwischen diesen Informationsräumen zu verstehen. Aufbauend auf der Bedrohungsanalyse werden im weiteren Verlauf die Nachrichtenflüsse der operationellen Netzknoten auf Verstöße gegen Sicherheitsrichtlinien analysiert und die Ergebnisse mit Hilfe des Sicherheitsdatenflussdiagramms anonymisiert dargestellt. Durch Anonymisierung der Sicherheitsdatenflussdiagramme ist ein Austausch mit externen Experten zur Diskussion von Sicherheitsproblematiken möglich. Der dritte Teil der Arbeit zeigt, wie umfangreiche Protokolldaten der Nachrichtenflüsse dahingehend untersucht werden können, ob eine Reduzierung der Menge an Daten möglich ist. Dazu wird die Theorie der groben Mengen aus der Unsicherheitstheorie genutzt. Dieser Ansatz wird in einer Fallstudie, auch unter Berücksichtigung von möglichen auftretenden Anomalien getestet und ermittelt, welche Attribute in Protokolldaten am ehesten redundant sind. N2 - Risks to cyber resources can arise from unintentional or deliberate threats. These include insider threats from dissatisfied or negligent employees and partners, escalating and emerging threats from around the world, the evolving nature of attack technologies, and the emergence of new and destructive attacks. Information technology now plays a decisive role in all areas of life, including the military. Ineffective protection of cyber resources can facilitate security incidents and cyberattacks that disrupt critical operations, lead to inappropriate access, disclosure, alteration or destruction of sensitive information, and endanger national security, economic welfare and public health and safety. However, it is often unclear which threats are present and which of the critical system resources are particularly at risk. In this dissertation different analysis methods for threats in military information technology are proposed and tested in real environments. This refers to infrastructures, IT systems, networks and applications that process classified information/state secrets, such as in military or governmental organizations. The special characteristic of these organizations is the concept of classification zones in which different data elements, such as paper documents and computer files, are classified according to their security sensitivity, e.g. „TOP SECRET“, „SECRET“, „CONFIDENTIAL“, „RESTRICTED“ or „UNCLASSIFIED“. The peculiarity of this work is the access to classified information from different classification zones and the process of releasing it. Each publication created during the work was discussed, proofread and approved by members of the organization, so that no classified information is released to the public. The dissertation first describes threat classification schemes and attacker strategies in order to derive a holistic, strategy-based threat model for organizations. In the further course, the creation and analysis of a security data flow diagram is defined, which is used to identify operational network nodes in classification zones, which are particularly endangered due to the threats. The special, novel representation makes it possible to understand permitted and prohibited information flows within and between these classification zones. Based on the threat analysis, the message flows of the operational network nodes are analyzed for violations of security policies and the results are presented anonymously using the security data flow diagram. By anonymizing the security data flow diagrams, it is possible to exchange information with external experts to discuss security problems. The third part of the dissertation shows how extensive log data of message flows can be examined to determine whether a reduction in the amount of data is possible. The rough set theory from the uncertainty theory is used for this purpose. This approach is tested in a case study, also taking into account possible anomalies, and determines which attributes are most likely to be redundant in the protocol data. KW - Informationsraum KW - classification zone KW - Bedrohungsmodell KW - threat model KW - Informationsflüsse KW - information flows KW - sichere Datenflussdiagramme (DFDsec) KW - secure data flow diagrams (DFDsec) KW - Informationsraumverletzungen KW - classification zone violations KW - grobe Protokolle KW - rough logs KW - Bedrohungsanalyse KW - threat analysis Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-441608 ER - TY - JOUR A1 - Şahin, Muhittin A1 - Egloffstein, Marc A1 - Bothe, Max A1 - Rohloff, Tobias A1 - Schenk, Nathanael A1 - Schwerer, Florian A1 - Ifenthaler, Dirk T1 - Behavioral Patterns in Enterprise MOOCs at openSAP JF - EMOOCs 2021 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517350 SN - 978-3-86956-512-5 VL - 2021 SP - 281 EP - 288 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Matthies, Christoph A1 - Teusner, Ralf A1 - Hesse, Günter T1 - Beyond Surveys BT - Analyzing software development artifacts to assess teaching efforts T2 - 2018 IEEE Frontiers in Education (FIE) Conference KW - software engineering KW - capstone course KW - development artifacts KW - Kanban KW - Scrum KW - Educational Data Mining Y1 - 2018 SN - 978-1-5386-1174-6 SN - 978-1-5386-1175-3 SN - 0190-5848 PB - IEEE CY - New York ER - TY - BOOK A1 - Meinel, Christoph A1 - Gayvoronskaya, Tatiana A1 - Schnjakin, Maxim T1 - Blockchain BT - hype or innovation N2 - The term blockchain has recently become a buzzword, but only few know what exactly lies behind this approach. According to a survey, issued in the first quarter of 2017, the term is only known by 35 percent of German medium-sized enterprise representatives. However, the blockchain technology is very interesting for the mass media because of its rapid development and global capturing of different markets. For example, many see blockchain technology either as an all-purpose weapon— which only a few have access to—or as a hacker technology for secret deals in the darknet. The innovation of blockchain technology is found in its successful combination of already existing approaches: such as decentralized networks, cryptography, and consensus models. This innovative concept makes it possible to exchange values in a decentralized system. At the same time, there is no requirement for trust between its nodes (e.g. users). With this study the Hasso Plattner Institute would like to help readers form their own opinion about blockchain technology, and to distinguish between truly innovative properties and hype. The authors of the present study analyze the positive and negative properties of the blockchain architecture and suggest possible solutions, which can contribute to the efficient use of the technology. We recommend that every company define a clear target for the intended application, which is achievable with a reasonable cost-benefit ration, before deciding on this technology. Both the possibilities and the limitations of blockchain technology need to be considered. The relevant steps that must be taken in this respect are summarized /summed up for the reader in this study. Furthermore, this study elaborates on urgent problems such as the scalability of the blockchain, appropriate consensus algorithm and security, including various types of possible attacks and their countermeasures. New blockchains, for example, run the risk of reducing security, as changes to existing technology can lead to lacks in the security and failures. After discussing the innovative properties and problems of the blockchain technology, its implementation is discussed. There are a lot of implementation opportunities for companies available who are interested in the blockchain realization. The numerous applications have either their own blockchain as a basis or use existing and widespread blockchain systems. Various consortia and projects offer "blockchain-as-a-serviceänd help other companies to develop, test and deploy their own applications. This study gives a detailed overview of diverse relevant applications and projects in the field of blockchain technology. As this technology is still a relatively young and fast developing approach, it still lacks uniform standards to allow the cooperation of different systems and to which all developers can adhere. Currently, developers are orienting themselves to Bitcoin, Ethereum and Hyperledger systems, which serve as the basis for many other blockchain applications. The goal is to give readers a clear and comprehensive overview of blockchain technology and its capabilities. N2 - Der Begriff Blockchain ist in letzter Zeit zu einem Schlagwort geworden, aber nur wenige wissen, was sich genau dahinter verbirgt. Laut einer Umfrage, die im ersten Quartal 2017 veröffentlicht wurde, ist der Begriff nur bei 35 Prozent der deutschen Mittelständler bekannt. Dabei ist die Blockchain-Technologie durch ihre rasante Entwicklung und die globale Eroberung unterschiedlicher Märkte für Massenmedien sehr interessant. So sehen viele die Blockchain-Technologie entweder als eine Allzweckwaffe, zu der aber nur wenige einen Zugang haben, oder als eine Hacker-Technologie für geheime Geschäfte im Darknet. Dabei liegt die Innovation der Blockchain-Technologie in ihrer erfolgreichen Zusammensetzung bereits vorhandener Ansätze: dezentrale Netzwerke, Kryptographie, Konsensfindungsmodelle. Durch das innovative Konzept wird ein Werte-Austausch in einem dezentralen System möglich. Dabei wird kein Vertrauen zwischen dessen Knoten (z.B. Nutzer) vorausgesetzt. Mit dieser Studie möchte das Hasso-Plattner-Institut den Lesern helfen, ihren eigenen Standpunkt zur Blockchain-Technologie zu finden und dabei dazwischen unterscheiden zu können, welche Eigenschaften wirklich innovativ und welche nichts weiter als ein Hype sind. Die Autoren der vorliegenden Arbeit analysieren positive und negative Eigenschaften, welche die Blockchain-Architektur prägen, und stellen mögliche Anpassungs- und Lösungsvorschläge vor, die zu einem effizienten Einsatz der Technologie beitragen können. Jedem Unternehmen, bevor es sich für diese Technologie entscheidet, wird dabei empfohlen, für den geplanten Anwendungszweck zunächst ein klares Ziel zu definieren, das mit einem angemessenen Kosten-Nutzen-Verhältnis angestrebt werden kann. Dabei sind sowohl die Möglichkeiten als auch die Grenzen der Blockchain-Technologie zu beachten. Die relevanten Schritte, die es in diesem Zusammenhang zu beachten gilt, fasst die Studie für die Leser übersichtlich zusammen. Es wird ebenso auf akute Fragestellungen wie Skalierbarkeit der Blockchain, geeigneter Konsensalgorithmus und Sicherheit eingegangen, darunter verschiedene Arten möglicher Angriffe und die entsprechenden Gegenmaßnahmen zu deren Abwehr. Neue Blockchains etwa laufen Gefahr, geringere Sicherheit zu bieten, da Änderungen an der bereits bestehenden Technologie zu Schutzlücken und Mängeln führen können. Nach Diskussion der innovativen Eigenschaften und Probleme der Blockchain-Technologie wird auf ihre Umsetzung eingegangen. Interessierten Unternehmen stehen viele Umsetzungsmöglichkeiten zur Verfügung. Die zahlreichen Anwendungen haben entweder eine eigene Blockchain als Grundlage oder nutzen bereits bestehende und weitverbreitete Blockchain-Systeme. Zahlreiche Konsortien und Projekte bieten „Blockchain-as-a-Service“ an und unterstützen andere Unternehmen beim Entwickeln, Testen und Bereitstellen von Anwendungen. Die Studie gibt einen detaillierten Überblick über zahlreiche relevante Einsatzbereiche und Projekte im Bereich der Blockchain-Technologie. Dadurch, dass sie noch relativ jung ist und sich schnell entwickelt, fehlen ihr noch einheitliche Standards, die Zusammenarbeit der verschiedenen Systeme erlauben und an die sich alle Entwickler halten können. Aktuell orientieren sich Entwickler an Bitcoin-, Ethereum- und Hyperledger-Systeme, diese dienen als Grundlage für viele weitere Blockchain-Anwendungen. Ziel ist, den Lesern einen klaren und umfassenden Überblick über die Blockchain-Technologie und deren Möglichkeiten zu vermitteln. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 124 KW - ACINQ KW - altchain KW - alternative chain KW - ASIC KW - atomic swap KW - Australian securities exchange KW - bidirectional payment channels KW - Bitcoin Core KW - bitcoins KW - BitShares KW - Blockchain Auth KW - blockchain consortium KW - cross-chain KW - inter-chain KW - blocks KW - blockchain KW - Blockstack ID KW - Blockstack KW - blumix platform KW - BTC KW - Byzantine Agreement KW - chain KW - cloud KW - Colored Coins KW - confirmation period KW - contest period KW - DAO KW - Delegated Proof-of-Stake KW - decentralized autonomous organization KW - Distributed Proof-of-Research KW - double hashing KW - DPoS KW - ECDSA KW - Eris KW - Ether KW - Ethereum KW - E-Wallet KW - Federated Byzantine Agreement KW - federated voting KW - FollowMyVote KW - Fork KW - Gridcoin KW - Hard Fork KW - Hashed Timelock Contracts KW - hashrate KW - identity management KW - smart contracts KW - Internet of Things KW - IoT KW - BCCC KW - Japanese Blockchain Consortium KW - consensus algorithm KW - consensus protocol KW - ledger assets KW - Lightning Network KW - Lock-Time-Parameter KW - merged mining KW - merkle root KW - micropayment KW - micropayment channels KW - Microsoft Azur KW - miner KW - mining KW - mining hardware KW - minting KW - Namecoin KW - NameID KW - NASDAQ KW - nonce KW - off-chain transaction KW - Onename KW - OpenBazaar KW - Oracles KW - Orphan Block KW - P2P KW - Peercoin KW - peer-to-peer network KW - pegged sidechains KW - PoB KW - PoS KW - PoW KW - Proof-of-Burn KW - Proof-of-Stake KW - Proof-of-Work KW - quorum slices KW - Ripple KW - rootstock KW - scarce tokens KW - difficulty KW - SCP KW - SHA KW - sidechain KW - Simplified Payment Verification KW - scalability of blockchain KW - Slock.it KW - Soft Fork KW - SPV KW - Steemit KW - Stellar Consensus Protocol KW - Storj KW - The Bitfury Group KW - transaction KW - Two-Way-Peg KW - The DAO KW - Unspent Transaction Output KW - contracts KW - Watson IoT KW - difficulty target KW - Zookos triangle KW - Blockchain-Konsortium R3 KW - blockchain-übergreifend KW - Blöcke KW - Blockkette KW - Blumix-Plattform KW - dezentrale autonome Organisation KW - doppelter Hashwert KW - Identitätsmanagement KW - intelligente Verträge KW - Internet der Dinge KW - Japanisches Blockchain-Konsortium KW - Kette KW - Konsensalgorithmus KW - Konsensprotokoll KW - Micropayment-Kanäle KW - Off-Chain-Transaktionen KW - Peer-to-Peer Netz KW - Schwierigkeitsgrad KW - Skalierbarkeit der Blockchain KW - Transaktion KW - Verträge KW - Zielvorgabe KW - Zookos Dreieck Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-414525 SN - 978-3-86956-441-8 SN - 1613-5652 SN - 2191-1665 IS - 124 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Richly, Keven A1 - Schlosser, Rainer A1 - Boissier, Martin T1 - Budget-conscious fine-grained configuration optimization for spatio-temporal applications JF - Proceedings of the VLDB Endowment N2 - Based on the performance requirements of modern spatio-temporal data mining applications, in-memory database systems are often used to store and process the data. To efficiently utilize the scarce DRAM capacities, modern database systems support various tuning possibilities to reduce the memory footprint (e.g., data compression) or increase performance (e.g., additional indexes). However, the selection of cost and performance balancing configurations is challenging due to the vast number of possible setups consisting of mutually dependent individual decisions. In this paper, we introduce a novel approach to jointly optimize the compression, sorting, indexing, and tiering configuration for spatio-temporal workloads. Further, we consider horizontal data partitioning, which enables the independent application of different tuning options on a fine-grained level. We propose different linear programming (LP) models addressing cost dependencies at different levels of accuracy to compute optimized tuning configurations for a given workload and memory budgets. To yield maintainable and robust configurations, we extend our LP-based approach to incorporate reconfiguration costs as well as a worst-case optimization for potential workload scenarios. Further, we demonstrate on a real-world dataset that our models allow to significantly reduce the memory footprint with equal performance or increase the performance with equal memory size compared to existing tuning heuristics. KW - General Earth and Planetary Sciences KW - Water Science and Technology KW - Geography, Planning and Development Y1 - 2022 U6 - https://doi.org/10.14778/3565838.3565858 SN - 2150-8097 VL - 15 IS - 13 SP - 4079 EP - 4092 PB - Association for Computing Machinery (ACM) CY - [New York] ER - TY - JOUR A1 - Möring, Sebastian A1 - de Mutiis, Marco T1 - Camera Ludica BT - Reflections on Photography in Video Games JF - Intermedia games - Games inter media : Video games and intermediality Y1 - 2019 SN - 978-1-5013-3051-3 SN - 978-1-5013-3049-0 SP - 69 EP - 93 PB - Bloomsbury academic CY - New York ER - TY - GEN A1 - Brinkmann, Maik A1 - Heine, Moreen T1 - Can Blockchain Leverage for New Public Governance? BT - a Conceptual Analysis on Process Level T2 - Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance N2 - New Public Governance (NPG) as a paradigm for collaborative forms of public service delivery and Blockchain governance are trending topics for researchers and practitioners alike. Thus far, each topic has, on the whole, been discussed separately. This paper presents the preliminary results of ongoing research which aims to shed light on the more concrete benefits of Blockchain for the purpose of NPG. For the first time, a conceptual analysis is conducted on process level to spot benefits and limitations of Blockchain-based governance. Per process element, Blockchain key characteristics are mapped to functional aspects of NPG from a governance perspective. The preliminary results show that Blockchain offers valuable support for governments seeking methods to effectively coordinate co-producing networks. However, the extent of benefits of Blockchain varies across the process elements. It becomes evident that there is a need for off-chain processes. It is, therefore, argued in favour of intensifying research on off-chain governance processes to better understand the implications for and influences on on-chain governance. KW - Blockchain KW - New Public Governance KW - Blockchain Governance KW - Co-production KW - Conceptual Fit KW - Blockchain-enabled Governance Y1 - 2019 SN - 978-1-4503-6644-1 U6 - https://doi.org/10.1145/3326365.3326409 SP - 338 EP - 341 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Neuböck, Kristina A1 - Linschinger, Nadine ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Central elements of knowledge and competence development with MOOCs BT - using the example of the OER-MOOC JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - To implement OERs at HEIs sustainably, not just technical infrastructure is required, but also well-trained staff. The University of Graz is in charge of an OER training program for university staff as part of the collaborative project Open Education Austria Advanced (OEAA) with the aim of ensuring long-term competence growth in the use and creation of OERs. The program consists of a MOOC and a guided blended learning format that was evaluated to find out which accompanying teaching and learning concepts can best facilitate targeted competence development. The evaluation of the program shows that learning videos, self-study assignments and synchronous sessions are most useful for the learning process. The results indicate that the creation of OERs is a complex process that can be undergone more effectively in the guided program. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624668 SP - 255 EP - 262 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Lorenz, Anja A1 - Bock, Stefanie A1 - Schulte-Ostermann, Juleka ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Challenges and proposals for introducing digital certificates in higher education infrastructures JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - Questions about the recognition of MOOCs within and outside higher education were already being raised in the early 2010s. Today, recognition decisions are still made more or less on a case-by-case basis. However, digital certification approaches are now emerging that could automate recognition processes. The technical development of the required machinereadable documents and infrastructures is already well advanced in some cases. The DigiCerts consortium has developed a solution based on a collective blockchain. There are ongoing and open discussions regarding the particular technology, but the institutional implementation of digital certificates raises further questions. A number of workshops have been held at the Institute for Interactive Systems at Technische Hochschule Lübeck, which have identified the need for new responsibilities for issuing certificates. It has also become clear that all members of higher education institutions need to develop skills in the use of digital certificates. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-624701 SP - 263 EP - 270 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Schlosser, Rainer A1 - Chenavaz, Régis Y. A1 - Dimitrov, Stanko T1 - Circular economy BT - joint dynamic pricing and recycling investments JF - International journal of production economics N2 - In a circular economy, the use of recycled resources in production is a key performance indicator for management. Yet, academic studies are still unable to inform managers on appropriate recycling and pricing policies. We develop an optimal control model integrating a firm's recycling rate, which can use both virgin and recycled resources in the production process. Our model accounts for recycling influence both at the supply- and demandsides. The positive effect of a firm's use of recycled resources diminishes over time but may increase through investments. Using general formulations for demand and cost, we analytically examine joint dynamic pricing and recycling investment policies in order to determine their optimal interplay over time. We provide numerical experiments to assess the existence of a steady-state and to calculate sensitivity analyses with respect to various model parameters. The analysis shows how to dynamically adapt jointly optimized controls to reach sustainability in the production process. Our results pave the way to sounder sustainable practices for firms operating within a circular economy. KW - Dynamic pricing KW - Recycling investments KW - Optimal control KW - General demand function KW - Circular economy Y1 - 2021 U6 - https://doi.org/10.1016/j.ijpe.2021.108117 SN - 0925-5273 SN - 1873-7579 VL - 236 PB - Elsevier CY - Amsterdam ER - TY - THES A1 - Alhosseini Almodarresi Yasin, Seyed Ali T1 - Classification, prediction and evaluation of graph neural networks on online social media platforms T1 - Klassifizierung, Vorhersage und Bewertung graphischer neuronaler Netze auf Online-Social-Media-Plattformen N2 - The vast amount of data generated on social media platforms have made them a valuable source of information for businesses, governments and researchers. Social media data can provide insights into user behavior, preferences, and opinions. In this work, we address two important challenges in social media analytics. Predicting user engagement with online content has become a critical task for content creators to increase user engagement and reach larger audiences. Traditional user engagement prediction approaches rely solely on features derived from the user and content. However, a new class of deep learning methods based on graphs captures not only the content features but also the graph structure of social media networks. This thesis proposes a novel Graph Neural Network (GNN) approach to predict user interaction with tweets. The proposed approach combines the features of users, tweets and their engagement graphs. The tweet text features are extracted using pre-trained embeddings from language models, and a GNN layer is used to embed the user in a vector space. The GNN model then combines the features and graph structure to predict user engagement. The proposed approach achieves an accuracy value of 94.22% in classifying user interactions, including likes, retweets, replies, and quotes. Another major challenge in social media analysis is detecting and classifying social bot accounts. Social bots are automated accounts used to manipulate public opinion by spreading misinformation or generating fake interactions. Detecting social bots is critical to prevent their negative impact on public opinion and trust in social media. In this thesis, we classify social bots on Twitter by applying Graph Neural Networks. The proposed approach uses a combination of both the features of a node and an aggregation of the features of a node’s neighborhood to classify social bot accounts. Our final results indicate a 6% improvement in the area under the curve score in the final predictions through the utilization of GNN. Overall, our work highlights the importance of social media data and the potential of new methods such as GNNs to predict user engagement and detect social bots. These methods have important implications for improving the quality and reliability of information on social media platforms and mitigating the negative impact of social bots on public opinion and discourse. N2 - Die riesige Menge an Daten, die auf Social-Media-Plattformen generiert wird, hat sie zu einer wertvollen Informationsquelle für Unternehmen, Regierungen und Forscher gemacht. Daten aus sozialen Medien können Einblicke in das Verhalten, die Vorlieben und die Meinungen der Nutzer geben. In dieser Arbeit befassen wir uns mit zwei wichtigen Herausforderungen im Bereich der Social-Media-Analytik. Die Vorhersage des Nutzerinteresses an Online-Inhalten ist zu einer wichtigen Aufgabe für die Ersteller von Inhalten geworden, um das Nutzerengagement zu steigern und ein größeres Publikum zu erreichen. Herkömmliche Ansätze zur Vorhersage des Nutzerengagements stützen sich ausschließlich auf Merkmale, die aus dem Nutzer und dem Inhalt abgeleitet werden. Eine neue Klasse von Deep-Learning-Methoden, die auf Graphen basieren, erfasst jedoch nicht nur die Inhaltsmerkmale, sondern auch die Graphenstruktur von Social-Media-Netzwerken. In dieser Arbeit wird ein neuartiger Graph Neural Network (GNN)-Ansatz zur Vorhersage der Nutzerinteraktion mit Tweets vorgeschlagen. Der vorgeschlagene Ansatz kombiniert die Merkmale von Nutzern, Tweets und deren Engagement-Graphen. Die Textmerkmale der Tweets werden mit Hilfe von vortrainierten Einbettungen aus Sprachmodellen extrahiert, und eine GNN-Schicht wird zur Einbettung des Nutzers in einen Vektorraum verwendet. Das GNN-Modell kombiniert dann die Merkmale und die Graphenstruktur, um das Nutzerengagement vorherzusagen. Der vorgeschlagene Ansatz erreicht eine Genauigkeit von 94,22% bei der Klassifizierung von Benutzerinteraktionen, einschließlich Likes, Retweets, Antworten und Zitaten. Eine weitere große Herausforderung bei der Analyse sozialer Medien ist die Erkennung und Klassifizierung von Social-Bot-Konten. Social Bots sind automatisierte Konten, die dazu dienen, die öffentliche Meinung zu manipulieren, indem sie Fehlinformationen verbreiten oder gefälschte Interaktionen erzeugen. Die Erkennung von Social Bots ist entscheidend, um ihre negativen Auswirkungen auf die öffentliche Meinung und das Vertrauen in soziale Medien zu verhindern. In dieser Arbeit klassifizieren wir Social Bots auf Twitter mit Hilfe von Graph Neural Networks. Der vorgeschlagene Ansatz verwendet eine Kombination aus den Merkmalen eines Knotens und einer Aggregation der Merkmale der Nachbarschaft eines Knotens, um Social-Bot-Konten zu klassifizieren. Unsere Endergebnisse zeigen eine 6%ige Verbesserung der Fläche unter der Kurve bei den endgültigen Vorhersagen durch die Verwendung von GNN. Insgesamt unterstreicht unsere Arbeit die Bedeutung von Social-Media-Daten und das Potenzial neuer Methoden wie GNNs zur Vorhersage des Nutzer-Engagements und zur Erkennung von Social Bots. Diese Methoden haben wichtige Auswirkungen auf die Verbesserung der Qualität und Zuverlässigkeit von Informationen auf Social-Media-Plattformen und die Abschwächung der negativen Auswirkungen von Social Bots auf die öffentliche Meinung und den Diskurs. KW - graph neural networks KW - social bot detection KW - user engagement KW - graphische neuronale Netze KW - Social Bots erkennen KW - Nutzer-Engagement Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-626421 ER - TY - JOUR A1 - Topali, Paraskevi A1 - Chounta, Irene-Angelica A1 - Ortega-Arranz, Alejandro A1 - Villagrá-Sobrino, Sara L. A1 - Martínez-Monés, Alejandra T1 - CoFeeMOOC-v.2 BT - Designing Contingent Feedback for Massive Open Online Courses JF - EMOOCs 2021 N2 - Providing adequate support to MOOC participants is often a challenging task due to massiveness of the learners’ population and the asynchronous communication among peers and MOOC practitioners. This workshop aims at discussing common learners’ problems reported in the literature and reflect on designing adequate feedback interventions with the use of learning data. Our aim is three-fold: a) to pinpoint MOOC aspects that impact the planning of feedback, b) to explore the use of learning data in designing feedback strategies, and c) to propose design guidelines for developing and delivering scaffolding interventions for personalized feedback in MOOCs. To do so, we will carry out hands-on activities that aim to involve participants in interpreting learning data and using them to design adaptive feedback. This workshop appeals to researchers, practitioners and MOOC stakeholders who aim to providing contextualized scaffolding. We envision that this workshop will provide insights for bridging the gap between pedagogical theory and practice when it comes to feedback interventions in MOOCs. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517241 SN - 978-3-86956-512-5 VL - 2021 SP - 209 EP - 217 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Staubitz, Thomas A1 - Meinel, Christoph T1 - Collaborative Learning in MOOCs - Approaches and Experiments T2 - 2018 IEEE Frontiers in Education (FIE) Conference N2 - This Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced. KW - MOOC KW - Collaborative learning KW - Peer assessment KW - Team based assignment KW - Teamwork Y1 - 2018 SN - 978-1-5386-1174-6 SN - 0190-5848 PB - IEEE CY - New York ER - TY - THES A1 - Quinzan, Francesco T1 - Combinatorial problems and scalability in artificial intelligence N2 - Modern datasets often exhibit diverse, feature-rich, unstructured data, and they are massive in size. This is the case of social networks, human genome, and e-commerce databases. As Artificial Intelligence (AI) systems are increasingly used to detect pattern in data and predict future outcome, there are growing concerns on their ability to process large amounts of data. Motivated by these concerns, we study the problem of designing AI systems that are scalable to very large and heterogeneous data-sets. Many AI systems require to solve combinatorial optimization problems in their course of action. These optimization problems are typically NP-hard, and they may exhibit additional side constraints. However, the underlying objective functions often exhibit additional properties. These properties can be exploited to design suitable optimization algorithms. One of these properties is the well-studied notion of submodularity, which captures diminishing returns. Submodularity is often found in real-world applications. Furthermore, many relevant applications exhibit generalizations of this property. In this thesis, we propose new scalable optimization algorithms for combinatorial problems with diminishing returns. Specifically, we focus on three problems, the Maximum Entropy Sampling problem, Video Summarization, and Feature Selection. For each problem, we propose new algorithms that work at scale. These algorithms are based on a variety of techniques, such as forward step-wise selection and adaptive sampling. Our proposed algorithms yield strong approximation guarantees, and the perform well experimentally. We first study the Maximum Entropy Sampling problem. This problem consists of selecting a subset of random variables from a larger set, that maximize the entropy. By using diminishing return properties, we develop a simple forward step-wise selection optimization algorithm for this problem. Then, we study the problem of selecting a subset of frames, that represent a given video. Again, this problem corresponds to a submodular maximization problem. We provide a new adaptive sampling algorithm for this problem, suitable to handle the complex side constraints imposed by the application. We conclude by studying Feature Selection. In this case, the underlying objective functions generalize the notion of submodularity. We provide a new adaptive sequencing algorithm for this problem, based on the Orthogonal Matching Pursuit paradigm. Overall, we study practically relevant combinatorial problems, and we propose new algorithms to solve them. We demonstrate that these algorithms are suitable to handle massive datasets. However, our analysis is not problem-specific, and our results can be applied to other domains, if diminishing return properties hold. We hope that the flexibility of our framework inspires further research into scalability in AI. N2 - Moderne Datensätze bestehen oft aus vielfältigen, funktionsreichen und unstrukturierten Daten, die zudem sehr groß sind. Dies gilt insbesondere für soziale Netzwerke, das menschliche Genom und E-Commerce Datenbanken. Mit dem zunehmenden Einsatz von künstlicher Intelligenz (KI) um Muster in den Daten zu erkennen und künftige Ergebnisse vorherzusagen, steigen auch die Bedenken hinsichtlich ihrer Fähigkeit große Datenmengen zu verarbeiten. Aus diesem Grund untersuchen wir das Problem der Entwicklung von KI-Systemen, die auf große und heterogene Datensätze skalieren. Viele KI-Systeme müssen während ihres Einsatzes kombinatorische Optimierungsprobleme lösen. Diese Optimierungsprobleme sind in der Regel NP-schwer und können zusätzliche Nebeneinschränkungen aufwiesen. Die Zielfunktionen dieser Probleme weisen jedoch oft zusätzliche Eigenschaften auf. Diese Eigenschaften können genutzt werden, um geeignete Optimierungsalgorithmen zu entwickeln. Eine dieser Eigenschaften ist das wohluntersuchte Konzept der Submodularität, das das Konzept des abnehmende Erträge beschreibt. Submodularität findet sich in vielen realen Anwendungen. Darüber hinaus weisen viele relevante An- wendungen Verallgemeinerungen dieser Eigenschaft auf. In dieser Arbeit schlagen wir neue skalierbare Algorithmen für kombinatorische Probleme mit abnehmenden Erträgen vor. Wir konzentrieren uns hierbei insbesondere auf drei Prob- leme: dem Maximum-Entropie-Stichproben Problem, der Videozusammenfassung und der Feature Selection. Für jedes dieser Probleme schlagen wir neue Algorithmen vor, die gut skalieren. Diese Algorithmen basieren auf verschiedenen Techniken wie der schrittweisen Vorwärtsauswahl und dem adaptiven sampling. Die von uns vorgeschlagenen Algorithmen bieten sehr gute Annäherungsgarantien und zeigen auch experimentell gute Leistung. Zunächst untersuchen wir das Maximum-Entropy-Sampling Problem. Dieses Problem besteht darin, zufällige Variablen aus einer größeren Menge auszuwählen, welche die Entropie maximieren. Durch die Verwendung der Eigenschaften des abnehmenden Ertrags entwickeln wir einen einfachen forward step-wise selection Optimierungsalgorithmus für dieses Problem. Anschließend untersuchen wir das Problem der Auswahl einer Teilmenge von Bildern, die ein bestimmtes Video repräsentieren. Dieses Problem entspricht einem submodularen Maximierungsproblem. Hierfür stellen wir einen neuen adaptiven Sampling-Algorithmus für dieses Problem zur Verfügung, das auch komplexe Nebenbedingungen erfüllen kann, welche durch die Anwendung entstehen. Abschließend untersuchen wir die Feature Selection. In diesem Fall verallgemeinern die zugrundeliegenden Zielfunktionen die Idee der submodularität. Wir stellen einen neuen adaptiven Sequenzierungsalgorithmus für dieses Problem vor, der auf dem Orthogonal Matching Pursuit Paradigma basiert. Insgesamt untersuchen wir praktisch relevante kombinatorische Probleme und schlagen neue Algorithmen vor, um diese zu lösen. Wir zeigen, dass diese Algorithmen für die Verarbeitung großer Datensätze geeignet sind. Unsere Auswertung ist jedoch nicht problemspezifisch und unsere Ergebnisse lassen sich auch auf andere Bereiche anwenden, sofern die Eigenschaften des abnehmenden Ertrags gelten. Wir hoffen, dass die Flexibilität unseres Frameworks die weitere Forschung im Bereich der Skalierbarkeit im Bereich KI anregt. KW - artificial intelligence KW - scalability KW - optimization KW - Künstliche Intelligenz KW - Optimierung Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-611114 ER - TY - JOUR A1 - Puri, Manish A1 - Varde, Aparna S. A1 - Melo, Gerard de T1 - Commonsense based text mining on urban policy JF - Language resources and evaluation N2 - Local laws on urban policy, i.e., ordinances directly affect our daily life in various ways (health, business etc.), yet in practice, for many citizens they remain impervious and complex. This article focuses on an approach to make urban policy more accessible and comprehensible to the general public and to government officials, while also addressing pertinent social media postings. Due to the intricacies of the natural language, ranging from complex legalese in ordinances to informal lingo in tweets, it is practical to harness human judgment here. To this end, we mine ordinances and tweets via reasoning based on commonsense knowledge so as to better account for pragmatics and semantics in the text. Ours is pioneering work in ordinance mining, and thus there is no prior labeled training data available for learning. This gap is filled by commonsense knowledge, a prudent choice in situations involving a lack of adequate training data. The ordinance mining can be beneficial to the public in fathoming policies and to officials in assessing policy effectiveness based on public reactions. This work contributes to smart governance, leveraging transparency in governing processes via public involvement. We focus significantly on ordinances contributing to smart cities, hence an important goal is to assess how well an urban region heads towards a smart city as per its policies mapping with smart city characteristics, and the corresponding public satisfaction. KW - Commonsense reasoning KW - Opinion mining KW - Ordinances KW - Smart cities KW - Social KW - media KW - Text mining Y1 - 2022 U6 - https://doi.org/10.1007/s10579-022-09584-6 SN - 1574-020X SN - 1574-0218 VL - 57 SP - 733 EP - 763 PB - Springer CY - Dordrecht [u.a.] ER - TY - JOUR A1 - Casel, Katrin A1 - Dreier, Jan A1 - Fernau, Henning A1 - Gobbert, Moritz A1 - Kuinke, Philipp A1 - Villaamil, Fernando Sánchez A1 - Schmid, Markus L. A1 - van Leeuwen, Erik Jan T1 - Complexity of independency and cliquy trees JF - Discrete applied mathematics N2 - An independency (cliquy) tree of an n-vertex graph G is a spanning tree of G in which the set of leaves induces an independent set (clique). We study the problems of minimizing or maximizing the number of leaves of such trees, and fully characterize their parameterized complexity. We show that all four variants of deciding if an independency/cliquy tree with at least/most l leaves exists parameterized by l are either Para-NP- or W[1]-hard. We prove that minimizing the number of leaves of a cliquy tree parameterized by the number of internal vertices is Para-NP-hard too. However, we show that minimizing the number of leaves of an independency tree parameterized by the number k of internal vertices has an O*(4(k))-time algorithm and a 2k vertex kernel. Moreover, we prove that maximizing the number of leaves of an independency/cliquy tree parameterized by the number k of internal vertices both have an O*(18(k))-time algorithm and an O(k 2(k)) vertex kernel, but no polynomial kernel unless the polynomial hierarchy collapses to the third level. Finally, we present an O(3(n) . f(n))-time algorithm to find a spanning tree where the leaf set has a property that can be decided in f (n) time and has minimum or maximum size. KW - independency tree KW - cliquy tree KW - parameterized complexity KW - Kernelization KW - algorithms KW - exact algorithms Y1 - 2018 U6 - https://doi.org/10.1016/j.dam.2018.08.011 SN - 0166-218X SN - 1872-6771 VL - 272 SP - 2 EP - 15 PB - Elsevier CY - Amsterdam [u.a.] ER - TY - BOOK A1 - Maximova, Maria A1 - Schneider, Sven A1 - Giese, Holger T1 - Compositional analysis of probabilistic timed graph transformation systems N2 - The analysis of behavioral models is of high importance for cyber-physical systems, as the systems often encompass complex behavior based on e.g. concurrent components with mutual exclusion or probabilistic failures on demand. The rule-based formalism of probabilistic timed graph transformation systems is a suitable choice when the models representing states of the system can be understood as graphs and timed and probabilistic behavior is important. However, model checking PTGTSs is limited to systems with rather small state spaces. We present an approach for the analysis of large scale systems modeled as probabilistic timed graph transformation systems by systematically decomposing their state spaces into manageable fragments. To obtain qualitative and quantitative analysis results for a large scale system, we verify that results obtained for its fragments serve as overapproximations for the corresponding results of the large scale system. Hence, our approach allows for the detection of violations of qualitative and quantitative safety properties for the large scale system under analysis. We consider a running example in which we model shuttles driving on tracks of a large scale topology and for which we verify that shuttles never collide and are unlikely to execute emergency brakes. In our evaluation, we apply an implementation of our approach to the running example. N2 - Die Analyse von Verhaltensmodellen ist für cyber-physikalische Systeme von hoher Bedeutung, da die Systeme häufig komplexes Verhalten umfassen, das z.B. parallele Komponenten mit gegenseitigem Ausschluss oder probabilistischen Fehlern bei Bedarf umfasst. Der regelbasierte Formalismus probabilistischer zeitgesteuerter Graphtransformationssysteme ist eine geeignete Wahl, wenn die Modelle, die Zustände des Systems darstellen, als Graphen verstanden werden können und zeitgesteuertes und probabilistisches Verhalten wichtig ist. Modelchecking von PTGTSs ist jedoch auf Systeme mit relativ kleinen Zustandsräumen beschränkt. Wir präsentieren einen Ansatz zur Analyse von Großsystemen, die als probabilistische zeitgesteuerte Graphtransformationssysteme modelliert wurden, indem ihre Zustandsräume systematisch in überschaubare Fragmente zerlegt werden. Um qualitative und quantitative Analyseergebnisse für ein Großsystem zu erhalten, überprüfen wir, ob die für seine Fragmente erhaltenen Ergebnisse als Überannäherungen für die entsprechenden Ergebnisse des Großsystems dienen. Unser Ansatz ermöglicht es daher, Verstöße gegen qualitative und quantitative Sicherheitseigenschaften für das untersuchte Großsystem zu erkennen. Wir betrachten ein Beispiel, in dem wir Shuttles modellieren, die auf Gleisen einer großen Topologie fahren, und für die wir überprüfen, dass Shuttles niemals kollidieren und wahrscheinlich keine Notbremsungen ausführen. In unserer Auswertung wenden wir eine Implementierung unseres Ansatzes auf das Beispiel an. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 133 KW - cyber-physical systems KW - graph transformation systems KW - qualitative analysis KW - quantitative analysis KW - probabilistic timed systems KW - compositional analysis KW - model checking KW - Cyber-physikalische Systeme KW - Graphentransformationssysteme KW - qualitative Analyse KW - quantitative Analyse KW - probabilistische zeitgesteuerte Systeme KW - Modellprüfung KW - kompositionale Analyse Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-490131 SN - 978-3-86956-501-9 SN - 1613-5652 SN - 2191-1665 IS - 133 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Perscheid, Cindy T1 - Comprior BT - Facilitating the implementation and automated benchmarking of prior knowledge-based feature selection approaches on gene expression data sets JF - BMC Bioinformatics N2 - Background Reproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness. Results We present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance. Conclusion Comprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness KW - Feature selection KW - Prior knowledge KW - Gene expression KW - Reproducible benchmarking Y1 - 2021 U6 - https://doi.org/10.1186/s12859-021-04308-z SN - 1471-2105 VL - 22 SP - 1 EP - 15 PB - Springer Nature CY - London ER - TY - GEN A1 - Perscheid, Cindy T1 - Comprior: facilitating the implementation and automated benchmarking of prior knowledge-based feature selection approaches on gene expression data sets T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Background Reproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness. Results We present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance. Conclusion Comprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 010 KW - Feature selection KW - Prior knowledge KW - Gene expression KW - Reproducible benchmarking Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-548943 SP - 1 EP - 15 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Razzaq, Misbah A1 - Kaminski, Roland A1 - Romero, Javier A1 - Schaub, Torsten H. A1 - Bourdon, Jeremie A1 - Guziolowski, Carito T1 - Computing diverse boolean networks from phosphoproteomic time series data T2 - Computational Methods in Systems Biology N2 - Logical modeling has been widely used to understand and expand the knowledge about protein interactions among different pathways. Realizing this, the caspo-ts system has been proposed recently to learn logical models from time series data. It uses Answer Set Programming to enumerate Boolean Networks (BNs) given prior knowledge networks and phosphoproteomic time series data. In the resulting sequence of solutions, similar BNs are typically clustered together. This can be problematic for large scale problems where we cannot explore the whole solution space in reasonable time. Our approach extends the caspo-ts system to cope with the important use case of finding diverse solutions of a problem with a large number of solutions. We first present the algorithm for finding diverse solutions and then we demonstrate the results of the proposed approach on two different benchmark scenarios in systems biology: (1) an artificial dataset to model TCR signaling and (2) the HPN-DREAM challenge dataset to model breast cancer cell lines. KW - Diverse solution enumeration KW - Answer set programming KW - Boolean Networks KW - Model checking KW - Time series data Y1 - 2018 SN - 978-3-319-99429-1 SN - 978-3-319-99428-4 U6 - https://doi.org/10.1007/978-3-319-99429-1_4 SN - 0302-9743 SN - 1611-3349 VL - 11095 SP - 59 EP - 74 PB - Springer CY - Berlin ER - TY - THES A1 - Limberger, Daniel T1 - Concepts and techniques for 3D-embedded treemaps and their application to software visualization T1 - Konzepte und Techniken für 3D-eingebettete Treemaps und ihre Anwendung auf Softwarevisualisierung N2 - This thesis addresses concepts and techniques for interactive visualization of hierarchical data using treemaps. It explores (1) how treemaps can be embedded in 3D space to improve their information content and expressiveness, (2) how the readability of treemaps can be improved using level-of-detail and degree-of-interest techniques, and (3) how to design and implement a software framework for the real-time web-based rendering of treemaps embedded in 3D. With a particular emphasis on their application, use cases from software analytics are taken to test and evaluate the presented concepts and techniques. Concerning the first challenge, this thesis shows that a 3D attribute space offers enhanced possibilities for the visual mapping of data compared to classical 2D treemaps. In particular, embedding in 3D allows for improved implementation of visual variables (e.g., by sketchiness and color weaving), provision of new visual variables (e.g., by physically based materials and in situ templates), and integration of visual metaphors (e.g., by reference surfaces and renderings of natural phenomena) into the three-dimensional representation of treemaps. For the second challenge—the readability of an information visualization—the work shows that the generally higher visual clutter and increased cognitive load typically associated with three-dimensional information representations can be kept low in treemap-based representations of both small and large hierarchical datasets. By introducing an adaptive level-of-detail technique, we cannot only declutter the visualization results, thereby reducing cognitive load and mitigating occlusion problems, but also summarize and highlight relevant data. Furthermore, this approach facilitates automatic labeling, supports the emphasis on data outliers, and allows visual variables to be adjusted via degree-of-interest measures. The third challenge is addressed by developing a real-time rendering framework with WebGL and accumulative multi-frame rendering. The framework removes hardware constraints and graphics API requirements, reduces interaction response times, and simplifies high-quality rendering. At the same time, the implementation effort for a web-based deployment of treemaps is kept reasonable. The presented visualization concepts and techniques are applied and evaluated for use cases in software analysis. In this domain, data about software systems, especially about the state and evolution of the source code, does not have a descriptive appearance or natural geometric mapping, making information visualization a key technology here. In particular, software source code can be visualized with treemap-based approaches because of its inherently hierarchical structure. With treemaps embedded in 3D, we can create interactive software maps that visually map, software metrics, software developer activities, or information about the evolution of software systems alongside their hierarchical module structure. Discussions on remaining challenges and opportunities for future research for 3D-embedded treemaps and their applications conclude the thesis. N2 - Diese Doktorarbeit behandelt Konzepte und Techniken zur interaktiven Visualisierung hierarchischer Daten mit Hilfe von Treemaps. Sie untersucht (1), wie Treemaps im 3D-Raum eingebettet werden können, um ihre Informationsinhalte und Ausdrucksfähigkeit zu verbessern, (2) wie die Lesbarkeit von Treemaps durch Techniken wie Level-of-Detail und Degree-of-Interest verbessert werden kann, und (3) wie man ein Software-Framework für das Echtzeit-Rendering von Treemaps im 3D-Raum entwirft und implementiert. Dabei werden Anwendungsfälle aus der Software-Analyse besonders betont und zur Verprobung und Bewertung der Konzepte und Techniken verwendet. Hinsichtlich der ersten Herausforderung zeigt diese Arbeit, dass ein 3D-Attributraum im Vergleich zu klassischen 2D-Treemaps verbesserte Möglichkeiten für die visuelle Kartierung von Daten bietet. Insbesondere ermöglicht die Einbettung in 3D eine verbesserte Umsetzung von visuellen Variablen (z.B. durch Skizzenhaftigkeit und Farbverwebungen), die Bereitstellung neuer visueller Variablen (z.B. durch physikalisch basierte Materialien und In-situ-Vorlagen) und die Integration visueller Metaphern (z.B. durch Referenzflächen und Darstellungen natürlicher Phänomene) in die dreidimensionale Darstellung von Treemaps. Für die zweite Herausforderung – die Lesbarkeit von Informationsvisualisierungen – zeigt die Arbeit, dass die allgemein höhere visuelle Unübersichtlichkeit und die damit einhergehende, erhöhte kognitive Belastung, die typischerweise mit dreidimensionalen Informationsdarstellungen verbunden sind, in Treemap-basierten Darstellungen sowohl kleiner als auch großer hierarchischer Datensätze niedrig gehalten werden können. Durch die Einführung eines adaptiven Level-of-Detail-Verfahrens lassen sich nicht nur die Visualisierungsergebnisse übersichtlicher gestalten, die kognitive Belastung reduzieren und Verdeckungsprobleme verringern, sondern auch relevante Daten zusammenfassen und hervorheben. Darüber hinaus erleichtert dieser Ansatz eine automatische Beschriftung, unterstützt die Hervorhebung von Daten-Ausreißern und ermöglicht die Anpassung von visuellen Variablen über Degree-of-Interest-Maße. Die dritte Herausforderung wird durch die Entwicklung eines Echtzeit-Rendering-Frameworks mit WebGL und akkumulativem Multi-Frame-Rendering angegangen. Das Framework hebt mehrere Hardwarebeschränkungen und Anforderungen an die Grafik-API auf, verkürzt die Reaktionszeiten auf Interaktionen und vereinfacht qualitativ hochwertiges Rendering. Gleichzeitig wird der Implementierungsaufwand für einen webbasierten Einsatz von Treemaps geringgehalten. Die vorgestellten Visualisierungskonzepte und -techniken werden für Anwendungsfälle in der Softwareanalyse eingesetzt und evaluiert. In diesem Bereich haben Daten über Softwaresysteme, insbesondere über den Zustand und die Evolution des Quellcodes, keine anschauliche Erscheinung oder natürliche geometrische Zuordnung, so dass die Informationsvisualisierung hier eine Schlüsseltechnologie darstellt. Insbesondere Softwarequellcode kann aufgrund seiner inhärenten hierarchischen Struktur mit Hilfe von Treemap-basierten Ansätzen visualisiert werden. Mit in 3D-eingebetteten Treemaps können wir interaktive Softwarelagekarten erstellen, die z.B. Softwaremetriken, Aktivitäten von Softwareentwickler*innen und Informationen über die Evolution von Softwaresystemen in ihrer hierarchischen Modulstruktur abbilden und veranschaulichen. Diskussionen über verbleibende Herausforderungen und Möglichkeiten für zukünftige Forschung zu 3D-eingebetteten Treemaps und deren Anwendungen schließen die Arbeit ab. KW - treemaps KW - software visualization KW - software analytics KW - web-based rendering KW - degree-of-interest techniques KW - labeling KW - 3D-embedding KW - interactive visualization KW - progressive rendering KW - hierarchical data KW - 3D-Einbettung KW - Interessengrad-Techniken KW - hierarchische Daten KW - interaktive Visualisierung KW - Beschriftung KW - progressives Rendering KW - Softwareanalytik KW - Softwarevisualisierung KW - Treemaps KW - Web-basiertes Rendering Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-632014 ER - TY - THES A1 - Richter, Rico T1 - Concepts and techniques for processing and rendering of massive 3D point clouds T1 - Konzepte und Techniken für die Verarbeitung und das Rendering von Massiven 3D-Punktwolken N2 - Remote sensing technology, such as airborne, mobile, or terrestrial laser scanning, and photogrammetric techniques, are fundamental approaches for efficient, automatic creation of digital representations of spatial environments. For example, they allow us to generate 3D point clouds of landscapes, cities, infrastructure networks, and sites. As essential and universal category of geodata, 3D point clouds are used and processed by a growing number of applications, services, and systems such as in the domains of urban planning, landscape architecture, environmental monitoring, disaster management, virtual geographic environments as well as for spatial analysis and simulation. While the acquisition processes for 3D point clouds become more and more reliable and widely-used, applications and systems are faced with more and more 3D point cloud data. In addition, 3D point clouds, by their very nature, are raw data, i.e., they do not contain any structural or semantics information. Many processing strategies common to GIS such as deriving polygon-based 3D models generally do not scale for billions of points. GIS typically reduce data density and precision of 3D point clouds to cope with the sheer amount of data, but that results in a significant loss of valuable information at the same time. This thesis proposes concepts and techniques designed to efficiently store and process massive 3D point clouds. To this end, object-class segmentation approaches are presented to attribute semantics to 3D point clouds, used, for example, to identify building, vegetation, and ground structures and, thus, to enable processing, analyzing, and visualizing 3D point clouds in a more effective and efficient way. Similarly, change detection and updating strategies for 3D point clouds are introduced that allow for reducing storage requirements and incrementally updating 3D point cloud databases. In addition, this thesis presents out-of-core, real-time rendering techniques used to interactively explore 3D point clouds and related analysis results. All techniques have been implemented based on specialized spatial data structures, out-of-core algorithms, and GPU-based processing schemas to cope with massive 3D point clouds having billions of points. All proposed techniques have been evaluated and demonstrated their applicability to the field of geospatial applications and systems, in particular for tasks such as classification, processing, and visualization. Case studies for 3D point clouds of entire cities with up to 80 billion points show that the presented approaches open up new ways to manage and apply large-scale, dense, and time-variant 3D point clouds as required by a rapidly growing number of applications and systems. N2 - Fernerkundungstechnologien wie luftgestütztes, mobiles oder terrestrisches Laserscanning und photogrammetrische Techniken sind grundlegende Ansätze für die effiziente, automatische Erstellung von digitalen Repräsentationen räumlicher Umgebungen. Sie ermöglichen uns zum Beispiel die Erzeugung von 3D-Punktwolken für Landschaften, Städte, Infrastrukturnetze und Standorte. 3D-Punktwolken werden als wesentliche und universelle Kategorie von Geodaten von einer wachsenden Anzahl an Anwendungen, Diensten und Systemen genutzt und verarbeitet, zum Beispiel in den Bereichen Stadtplanung, Landschaftsarchitektur, Umweltüberwachung, Katastrophenmanagement, virtuelle geographische Umgebungen sowie zur räumlichen Analyse und Simulation. Da die Erfassungsprozesse für 3D-Punktwolken immer zuverlässiger und verbreiteter werden, sehen sich Anwendungen und Systeme mit immer größeren 3D-Punktwolken-Daten konfrontiert. Darüber hinaus enthalten 3D-Punktwolken als Rohdaten von ihrer Art her keine strukturellen oder semantischen Informationen. Viele GIS-übliche Verarbeitungsstrategien, wie die Ableitung polygonaler 3D-Modelle, skalieren in der Regel nicht für Milliarden von Punkten. GIS reduzieren typischerweise die Datendichte und Genauigkeit von 3D-Punktwolken, um mit der immensen Datenmenge umgehen zu können, was aber zugleich zu einem signifikanten Verlust wertvoller Informationen führt. Diese Arbeit präsentiert Konzepte und Techniken, die entwickelt wurden, um massive 3D-Punktwolken effizient zu speichern und zu verarbeiten. Hierzu werden Ansätze für die Objektklassen-Segmentierung vorgestellt, um 3D-Punktwolken mit Semantik anzureichern; so lassen sich beispielsweise Gebäude-, Vegetations- und Bodenstrukturen identifizieren, wodurch die Verarbeitung, Analyse und Visualisierung von 3D-Punktwolken effektiver und effizienter durchführbar werden. Ebenso werden Änderungserkennungs- und Aktualisierungsstrategien für 3D-Punktwolken vorgestellt, mit denen Speicheranforderungen reduziert und Datenbanken für 3D-Punktwolken inkrementell aktualisiert werden können. Des Weiteren beschreibt diese Arbeit Out-of-Core Echtzeit-Rendering-Techniken zur interaktiven Exploration von 3D-Punktwolken und zugehöriger Analyseergebnisse. Alle Techniken wurden mit Hilfe spezialisierter räumlicher Datenstrukturen, Out-of-Core-Algorithmen und GPU-basierter Verarbeitungs-schemata implementiert, um massiven 3D-Punktwolken mit Milliarden von Punkten gerecht werden zu können. Alle vorgestellten Techniken wurden evaluiert und die Anwendbarkeit für Anwendungen und Systeme, die mit raumbezogenen Daten arbeiten, wurde insbesondere für Aufgaben wie Klassifizierung, Verarbeitung und Visualisierung demonstriert. Fallstudien für 3D-Punktwolken von ganzen Städten mit bis zu 80 Milliarden Punkten zeigen, dass die vorgestellten Ansätze neue Wege zur Verwaltung und Verwendung von großflächigen, dichten und zeitvarianten 3D-Punktwolken eröffnen, die von einer wachsenden Anzahl an Anwendungen und Systemen benötigt werden. KW - 3D point clouds KW - 3D-Punktwolken KW - real-time rendering KW - Echtzeit-Rendering KW - 3D visualization KW - 3D-Visualisierung KW - classification KW - Klassifizierung KW - change detection KW - Veränderungsanalyse KW - LiDAR KW - LiDAR KW - remote sensing KW - Fernerkundung KW - mobile mapping KW - Mobile-Mapping KW - Big Data KW - Big Data KW - GPU KW - GPU KW - laserscanning KW - Laserscanning Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-423304 ER - TY - GEN A1 - Combi, Carlo A1 - Oliboni, Barbara A1 - Weske, Mathias A1 - Zerbato, Francesca ED - Trujillo, JC Davis T1 - Conceptual modeling of processes and data BT - Connecting different perspectives T2 - Conceptual Modeling, ER 2018 N2 - Business processes constantly generate, manipulate, and consume data that are managed by organizational databases. Despite being central to process modeling and execution, the link between processes and data is often handled by developers when the process is implemented, thus leaving the connection unexplored during the conceptual design. In this paper, we introduce, formalize, and evaluate a novel conceptual view that bridges the gap between process and data models, and show some kinds of interesting insights that can be derived from this novel proposal. Y1 - 2018 SN - 978-3-030-00847-5 SN - 978-3-030-00846-8 U6 - https://doi.org/10.1007/978-3-030-00847-5_18 SN - 0302-9743 SN - 1611-3349 VL - 11157 SP - 236 EP - 250 PB - Springer CY - Cham ER - TY - JOUR A1 - Beirne, Elaine A1 - Nic Giolla Mhichíl, Mairéad A1 - Brown, Mark A1 - Mac Lochlainn, Conchúr T1 - Confidence Counts BT - Fostering Online Learning Self-Efficacy with a MOOC JF - EMOOCs 2021 N2 - The increasing reliance on online learning in higher education has been further expedited by the on-going Covid-19 pandemic. Students need to be supported as they adapt to this new learning environment. Research has established that learners with positive online learning self-efficacy beliefs are more likely to persevere and achieve their higher education goals when learning online. In this paper, we explore how MOOC design can contribute to the four sources of self-efficacy beliefs posited by Bandura [4]. Specifically, we will explore, drawing on learner reflections, whether design elements of the MOOC, The Digital Edge: Essentials for the Online Learner, provided participants with the necessary mastery experiences, vicarious experiences, verbal persuasion, and affective regulation opportunities, to evaluate and develop their online learning self-efficacy beliefs. Findings from a content analysis of discussion forum posts show that learners referenced three of the four information sources when reflecting on their experience of the MOOC. This paper illustrates the potential of MOOCs as a pedagogical tool for enhancing online learning self-efficacy among students. Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517220 SN - 978-3-86956-512-5 VL - 2021 SP - 201 EP - 208 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Galka, Andreas A1 - Moontaha, Sidratul A1 - Siniatchkin, Michael T1 - Constrained expectation maximisation algorithm for estimating ARMA models in state space representation JF - EURASIP journal on advances in signal processing N2 - This paper discusses the fitting of linear state space models to given multivariate time series in the presence of constraints imposed on the four main parameter matrices of these models. Constraints arise partly from the assumption that the models have a block-diagonal structure, with each block corresponding to an ARMA process, that allows the reconstruction of independent source components from linear mixtures, and partly from the need to keep models identifiable. The first stage of parameter fitting is performed by the expectation maximisation (EM) algorithm. Due to the identifiability constraint, a subset of the diagonal elements of the dynamical noise covariance matrix needs to be constrained to fixed values (usually unity). For this kind of constraints, so far, no closed-form update rules were available. We present new update rules for this situation, both for updating the dynamical noise covariance matrix directly and for updating a matrix square-root of this matrix. The practical applicability of the proposed algorithm is demonstrated by a low-dimensional simulation example. The behaviour of the EM algorithm, as observed in this example, illustrates the well-known fact that in practical applications, the EM algorithm should be combined with a different algorithm for numerical optimisation, such as a quasi-Newton algorithm. KW - Kalman filtering KW - state space modelling KW - expectation maximisation algorithm Y1 - 2020 U6 - https://doi.org/10.1186/s13634-020-00678-3 SN - 1687-6180 VL - 2020 IS - 1 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Söchting, Maximilian A1 - Trapp, Matthias T1 - Controlling image-stylization techniques using eye tracking JF - Science and Technology Publications N2 - With the spread of smart phones capable of taking high-resolution photos and the development of high-speed mobile data infrastructure, digital visual media is becoming one of the most important forms of modern communication. With this development, however, also comes a devaluation of images as a media form with the focus becoming the frequency at which visual content is generated instead of the quality of the content. In this work, an interactive system using image-abstraction techniques and an eye tracking sensor is presented, which allows users to experience diverting and dynamic artworks that react to their eye movement. The underlying modular architecture enables a variety of different interaction techniques that share common design principles, making the interface as intuitive as possible. The resulting experience allows users to experience a game-like interaction in which they aim for a reward, the artwork, while being held under constraints, e.g., not blinking. The co nscious eye movements that are required by some interaction techniques hint an interesting, possible future extension for this work into the field of relaxation exercises and concentration training. KW - Eye-tracking KW - Image Abstraction KW - Image Processing KW - Artistic Image Stylization KW - Interactive Media Y1 - 2020 SN - 2184-4321 PB - Springer CY - Berlin ER - TY - GEN A1 - Söchting, Maximilian A1 - Trapp, Matthias T1 - Controlling image-stylization techniques using eye tracking T2 - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - With the spread of smart phones capable of taking high-resolution photos and the development of high-speed mobile data infrastructure, digital visual media is becoming one of the most important forms of modern communication. With this development, however, also comes a devaluation of images as a media form with the focus becoming the frequency at which visual content is generated instead of the quality of the content. In this work, an interactive system using image-abstraction techniques and an eye tracking sensor is presented, which allows users to experience diverting and dynamic artworks that react to their eye movement. The underlying modular architecture enables a variety of different interaction techniques that share common design principles, making the interface as intuitive as possible. The resulting experience allows users to experience a game-like interaction in which they aim for a reward, the artwork, while being held under constraints, e.g., not blinking. The co nscious eye movements that are required by some interaction techniques hint an interesting, possible future extension for this work into the field of relaxation exercises and concentration training. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 7 KW - eye-tracking KW - image abstraction KW - image processing KW - artistic image stylization KW - interactive media Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-524717 IS - 7 ER - TY - GEN A1 - Perlich, Anja A1 - Meinel, Christoph T1 - Cooperative Note-Taking in Psychotherapy Sessions BT - an evaluation of the T2 - 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom) N2 - In the course of patient treatments, psychotherapists aim to meet the challenges of being both a trusted, knowledgeable conversation partner and a diligent documentalist. We are developing the digital whiteboard system Tele-Board MED (TBM), which allows the therapist to take digital notes during the session together with the patient. This study investigates what therapists are experiencing when they document with TBM in patient sessions for the first time and whether this documentation saves them time when writing official clinical documents. As the core of this study, we conducted four anamnesis session dialogues with behavior psychotherapists and volunteers acting in the role of patients. Following a mixed-method approach, the data collection and analysis involved self-reported emotion samples, user experience curves and questionnaires. We found that even in the very first patient session with TBM, therapists come to feel comfortable, develop a positive feeling and can concentrate on the patient. Regarding administrative documentation tasks, we found with the TBM report generation feature the therapists save 60% of the time they normally spend on writing case reports to the health insurance. KW - user experience KW - emotion measurement KW - computer-mediated therapy KW - behavior psychotherapy KW - human-computer interaction KW - medical documentation KW - note-taking Y1 - 2018 SN - 978-1-5386-4294-8 PB - IEEE CY - New York ER - TY - JOUR A1 - Wittig, Alice A1 - Miranda, Fabio Malcher A1 - Hölzer, Martin A1 - Altenburg, Tom A1 - Bartoszewicz, Jakub Maciej A1 - Beyvers, Sebastian A1 - Dieckmann, Marius Alfred A1 - Genske, Ulrich A1 - Giese, Sven Hans-Joachim A1 - Nowicka, Melania A1 - Richard, Hugues A1 - Schiebenhoefer, Henning A1 - Schmachtenberg, Anna-Juliane A1 - Sieben, Paul A1 - Tang, Ming A1 - Tembrockhaus, Julius A1 - Renard, Bernhard Y. A1 - Fuchs, Stephan T1 - CovRadar BT - continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance JF - Bioinformatics N2 - The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast. Y1 - 2022 U6 - https://doi.org/10.1093/bioinformatics/btac411 SN - 1367-4803 SN - 1367-4811 VL - 38 IS - 17 SP - 4223 EP - 4225 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Belaid, Mohamed Karim A1 - Rabus, Maximilian A1 - Krestel, Ralf T1 - CrashNet BT - an encoder-decoder architecture to predict crash test outcomes JF - Data mining and knowledge discovery N2 - Destructive car crash tests are an elaborate, time-consuming, and expensive necessity of the automotive development process. Today, finite element method (FEM) simulations are used to reduce costs by simulating car crashes computationally. We propose CrashNet, an encoder-decoder deep neural network architecture that reduces costs further and models specific outcomes of car crashes very accurately. We achieve this by formulating car crash events as time series prediction enriched with a set of scalar features. Traditional sequence-to-sequence models are usually composed of convolutional neural network (CNN) and CNN transpose layers. We propose to concatenate those with an MLP capable of learning how to inject the given scalars into the output time series. In addition, we replace the CNN transpose with 2D CNN transpose layers in order to force the model to process the hidden state of the set of scalars as one time series. The proposed CrashNet model can be trained efficiently and is able to process scalars and time series as input in order to infer the results of crash tests. CrashNet produces results faster and at a lower cost compared to destructive tests and FEM simulations. Moreover, it represents a novel approach in the car safety management domain. KW - Predictive models KW - Time series analysis KW - Supervised deep neural KW - networks KW - Car safety management Y1 - 2021 U6 - https://doi.org/10.1007/s10618-021-00761-9 SN - 1384-5810 SN - 1573-756X VL - 35 IS - 4 SP - 1688 EP - 1709 PB - Springer CY - Dordrecht ER - TY - GEN A1 - Bruechner, Dominik A1 - Renz, Jan A1 - Klingbeil, Mandy T1 - Creating a Framework for User-Centered Development and Improvement of Digital Education T2 - Scale N2 - We investigate how the technology acceptance and learning experience of the digital education platform HPI Schul-Cloud (HPI School Cloud) for German secondary school teachers can be improved by proposing a user-centered research and development framework. We highlight the importance of developing digital learning technologies in a user-centered way to take differences in the requirements of educators and students into account. We suggest applying qualitative and quantitative methods to build a solid understanding of a learning platform's users, their needs, requirements, and their context of use. After concept development and idea generation of features and areas of opportunity based on the user research, we emphasize on the application of a multi-attribute utility analysis decision-making framework to prioritize ideas rationally, taking results of user research into account. Afterward, we recommend applying the principle build-learn-iterate to build prototypes in different resolutions while learning from user tests and improving the selected opportunities. Last but not least, we propose an approach for continuous short- and long-term user experience controlling and monitoring, extending existing web- and learning analytics metrics. KW - learning platform KW - user experience KW - evaluation KW - HPI Schul-Cloud KW - user research framework KW - user-centered design Y1 - 2019 SN - 978-1-4503-6804-9 U6 - https://doi.org/10.1145/3330430.3333644 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Thienen, Julia von A1 - Weinstein, Theresa Julia A1 - Meinel, Christoph T1 - Creative metacognition in design thinking BT - exploring theories, educational practices, and their implications for measurement JF - Frontiers in psychology N2 - Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition. KW - accuracy KW - creativity KW - design thinking KW - education KW - measurement KW - metacognition KW - innovation KW - framework Y1 - 2023 U6 - https://doi.org/10.3389/fpsyg.2023.1157001 SN - 1664-1078 VL - 14 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Bin Tareaf, Raad A1 - Berger, Philipp A1 - Hennig, Patrick A1 - Meinel, Christoph T1 - Cross-platform personality exploration system for online social networks BT - Facebook vs. Twitter JF - Web intelligence N2 - Social networking sites (SNS) are a rich source of latent information about individual characteristics. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, commercial brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. Predictive evaluation on brands' accounts reveals that Facebook platform provides a slight advantage over Twitter platform in offering more self-disclosure for users' to express their emotions especially their demographic and psychological traits. Results also confirm the wider perspective that the same social media account carry a quite similar and comparable personality scores over different social media platforms. For evaluating our prediction results on actual brands' accounts, we crawled the Facebook API and Twitter API respectively for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions. KW - Big Five model KW - personality prediction KW - brand personality KW - machine KW - learning KW - social media analysis Y1 - 2020 U6 - https://doi.org/10.3233/WEB-200427 SN - 2405-6456 SN - 2405-6464 VL - 18 IS - 1 SP - 35 EP - 51 PB - IOS Press CY - Amsterdam ER - TY - GEN A1 - Torkura, Kennedy A. A1 - Sukmana, Muhammad Ihsan Haikal A1 - Strauss, Tim A1 - Graupner, Hendrik A1 - Cheng, Feng A1 - Meinel, Christoph T1 - CSBAuditor BT - proactive security risk analysis for cloud storage broker systems T2 - 17th International Symposium on Network Computing and Applications (NCA) N2 - Cloud Storage Brokers (CSB) provide seamless and concurrent access to multiple Cloud Storage Services (CSS) while abstracting cloud complexities from end-users. However, this multi-cloud strategy faces several security challenges including enlarged attack surfaces, malicious insider threats, security complexities due to integration of disparate components and API interoperability issues. Novel security approaches are imperative to tackle these security issues. Therefore, this paper proposes CSBAuditor, a novel cloud security system that continuously audits CSB resources, to detect malicious activities and unauthorized changes e.g. bucket policy misconfigurations, and remediates these anomalies. The cloud state is maintained via a continuous snapshotting mechanism thereby ensuring fault tolerance. We adopt the principles of chaos engineering by integrating Broker Monkey, a component that continuously injects failure into our reference CSB system, Cloud RAID. Hence, CSBAuditor is continuously tested for efficiency i.e. its ability to detect the changes injected by Broker Monkey. CSBAuditor employs security metrics for risk analysis by computing severity scores for detected vulnerabilities using the Common Configuration Scoring System, thereby overcoming the limitation of insufficient security metrics in existing cloud auditing schemes. CSBAuditor has been tested using various strategies including chaos engineering failure injection strategies. Our experimental evaluation validates the efficiency of our approach against the aforementioned security issues with a detection and recovery rate of over 96 %. KW - Cloud-Security KW - Cloud Audit KW - Security Metrics KW - Security Risk Assessment KW - Secure Configuration Y1 - 2018 SN - 978-1-5386-7659-2 U6 - https://doi.org/10.1109/NCA.2018.8548329 PB - IEEE CY - New York ER - TY - GEN A1 - Loster, Michael A1 - Naumann, Felix A1 - Ehmueller, Jan A1 - Feldmann, Benjamin T1 - CurEx BT - a system for extracting, curating, and exploring domain-specific knowledge graphs from text T2 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management N2 - The integration of diverse structured and unstructured information sources into a unified, domain-specific knowledge base is an important task in many areas. A well-maintained knowledge base enables data analysis in complex scenarios, such as risk analysis in the financial sector or investigating large data leaks, such as the Paradise or Panama papers. Both the creation of such knowledge bases, as well as their continuous maintenance and curation involves many complex tasks and considerable manual effort. With CurEx, we present a modular system that allows structured and unstructured data sources to be integrated into a domain-specific knowledge base. In particular, we (i) enable the incremental improvement of each individual integration component; (ii) enable the selective generation of multiple knowledge graphs from the information contained in the knowledge base; and (iii) provide two distinct user interfaces tailored to the needs of data engineers and end-users respectively. The former has curation capabilities and controls the integration process, whereas the latter focuses on the exploration of the generated knowledge graph. Y1 - 2018 SN - 978-1-4503-6014-2 U6 - https://doi.org/10.1145/3269206.3269229 SP - 1883 EP - 1886 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Omotosho, Adebayo A1 - Ayegba, Peace A1 - Emuoyibofarhe, Justice A1 - Meinel, Christoph T1 - Current State of ICT in Healthcare Delivery in Developing Countries JF - International Journal of Online and Biomedical Engineering N2 - Electronic health is one of the most popular applications of information and communication technologies and it has contributed immensely to health delivery through the provision of quality health service and ubiquitous access at a lower cost. Even though this mode of health service is increasingly becoming known or used in developing nations, these countries are faced with a myriad of challenges when implementing and deploying e-health services on both small and large scale. It is estimated that the Africa population alone carries the highest percentage of the world’s global diseases despite its certain level of e-health adoption. This paper aims at analyzing the progress so far and the current state of e-health in developing countries particularly Africa and propose a framework for further improvement. KW - E-health KW - developing countries KW - framework KW - ICT KW - healthcare Y1 - 2019 U6 - https://doi.org/10.3991/ijoe.v15i08.10294 SN - 2626-8493 VL - 15 IS - 8 SP - 91 EP - 107 PB - Kassel University Press CY - Kassel ER - TY - THES A1 - Koumarelas, Ioannis T1 - Data preparation and domain-agnostic duplicate detection N2 - Successfully completing any data science project demands careful consideration across its whole process. Although the focus is often put on later phases of the process, in practice, experts spend more time in earlier phases, preparing data, to make them consistent with the systems' requirements or to improve their models' accuracies. Duplicate detection is typically applied during the data cleaning phase, which is dedicated to removing data inconsistencies and improving the overall quality and usability of data. While data cleaning involves a plethora of approaches to perform specific operations, such as schema alignment and data normalization, the task of detecting and removing duplicate records is particularly challenging. Duplicates arise when multiple records representing the same entities exist in a database. Due to numerous reasons, spanning from simple typographical errors to different schemas and formats of integrated databases. Keeping a database free of duplicates is crucial for most use-cases, as their existence causes false negatives and false positives when matching queries against it. These two data quality issues have negative implications for tasks, such as hotel booking, where users may erroneously select a wrong hotel, or parcel delivery, where a parcel can get delivered to the wrong address. Identifying the variety of possible data issues to eliminate duplicates demands sophisticated approaches. While research in duplicate detection is well-established and covers different aspects of both efficiency and effectiveness, our work in this thesis focuses on the latter. We propose novel approaches to improve data quality before duplicate detection takes place and apply the latter in datasets even when prior labeling is not available. Our experiments show that improving data quality upfront can increase duplicate classification results by up to 19%. To this end, we propose two novel pipelines that select and apply generic as well as address-specific data preparation steps with the purpose of maximizing the success of duplicate detection. Generic data preparation, such as the removal of special characters, can be applied to any relation with alphanumeric attributes. When applied, data preparation steps are selected only for attributes where there are positive effects on pair similarities, which indirectly affect classification, or on classification directly. Our work on addresses is twofold; first, we consider more domain-specific approaches to improve the quality of values, and, second, we experiment with known and modified versions of similarity measures to select the most appropriate per address attribute, e.g., city or country. To facilitate duplicate detection in applications where gold standard annotations are not available and obtaining them is not possible or too expensive, we propose MDedup. MDedup is a novel, rule-based, and fully automatic duplicate detection approach that is based on matching dependencies. These dependencies can be used to detect duplicates and can be discovered using state-of-the-art algorithms efficiently and without any prior labeling. MDedup uses two pipelines to first train on datasets with known labels, learning to identify useful matching dependencies, and then be applied on unseen datasets, regardless of any existing gold standard. Finally, our work is accompanied by open source code to enable repeatability of our research results and application of our approaches to other datasets. N2 - Die erfolgreiche Durchführung eines datenwissenschaftlichen Projekts erfordert eine Reihe sorgfältiger Abwägungen, die während des gesamten Prozessesverlaufs zu treffen sind. Obwohl sich der Schwerpunkt oft auf spätere Prozessphasen konzentriert, verbringen Experten in der Praxis jedoch einen Großteil ihrer Zeit in frühen Projektphasen in denen sie Daten aufbereiten, um sie mit den Anforderungen vorhandener Systeme in Einklang zu bringen oder die Genauigkeit ihrer Modelle zu verbessern. Die Duplikaterkennung wird üblicherweise während der Datenbereinigungsphase durchgeführt, sie dient der Beseitigung von Dateninkonsistenzen und somit der Verbesserung von Gesamtqualität und Benutzerfreundlichkeit der Daten. Während die Datenbereinigung eine Vielzahl von Ansätzen zur Durchführung spezifischer Operationen wie etwa dem Schema-Abgleich und der Datennormalisierung umfasst, stellt die Identifizierung und Entfernung doppelter Datensätze eine besondere Herausforderung dar. Dabei entstehen Duplikate, wenn mehrere Datensätze, welche die gleichen Entitäten repräsentieren, in einer Datenbank vorhanden sind. Die Gründe dafür sind vielfältig und reichen von einfachen Schreibfehlern bis hin zu unterschiedlichen Schemata und Formaten integrierter Datenbanken. Eine Datenbank duplikatfrei zu halten, ist für die meisten Anwendungsfälle von entscheidender Bedeutung, da ihre Existenz zu falschen Negativ- und Falsch-Positiv-Abfragen führt. So können sich derartige Datenqualitätsprobleme negativ auf Aufgaben wie beispielsweise Hotelbuchungen oder Paketzustellungen auswirken, was letztlich dazu führen kann, dass Benutzer ein falsches Hotel buchen, oder Pakete an eine falsche Adresse geliefert werden. Um ein breites Spektrum potenzieller Datenprobleme zu identifizieren, deren Lösung die Beseitigung von Duplikaten erleichtert, sind eine Reihe ausgefeilter Ansätze erforderlich. Obgleich der Forschungsbereich der Duplikaterkennung mit der Untersuchung verschiedenster Effizienz und Effektivitätsaspekte bereits gut etabliert ist, konzentriert sich diese Arbeit auf letztgenannte Aspekte. Wir schlagen neue Ansätze zur Verbesserung der Datenqualität vor, die vor der Duplikaterkennung erfolgen, und wenden letztere auf Datensätze an, selbst wenn diese über keine im Vorfeld erstellten Annotationen verfügen. Unsere Experimente zeigen, dass durch eine im Vorfeld verbesserte Datenqualität die Ergebnisse der sich anschließenden Duplikatklassifizierung um bis zu 19% verbessert werden können. Zu diesem Zweck schlagen wir zwei neuartige Pipelines vor, die sowohl generische als auch adressspezifische Datenaufbereitungsschritte auswählen und anwenden, um den Erfolg der Duplikaterkennung zu maximieren. Die generische Datenaufbereitung, wie z.B. die Entfernung von Sonderzeichen, kann auf jede Relation mit alphanumerischen Attributen angewendet werden. Bei entsprechender Anwendung werden Datenaufbereitungsschritte nur für Attribute ausgewählt, bei denen sich positive Auswirkungen auf Paarähnlichkeiten ergeben, welche sich direkt oder indirekt auf die Klassifizierung auswirken. Unsere Arbeit an Adressen umfasst zwei Aspekte: erstens betrachten wir mehr domänenspezifische Ansätze zur Verbesserung der Adressqualität, zweitens experimentieren wir mit bekannten und modifizierten Versionen verschiedener Ähnlichkeitsmaße, um infolgedessen das am besten geeignete Ähnlichkeitsmaß für jedes Adressattribut, z.B. Stadt oder Land, zu bestimmen. Um die Erkennung von Duplikaten bei Anwendungen zu erleichtern, in denen Goldstandard-Annotationen nicht zur Verfügung stehen und deren Beschaffung aus Kostengründen nicht möglich ist, schlagen wir MDedup vor. MDedup ist ein neuartiger, regelbasierter und vollautomatischer Ansatz zur Dublikaterkennung, der auf Matching Dependencies beruht. Diese Abhängigkeiten können zur Erkennung von Duplikaten genutzt und mit Hilfe modernster Algorithmen effizient ohne vorhergehenden Annotationsaufwand entdeckt werden. MDedup verwendet zwei Pipelines, um zunächst auf annotierten Datensätzen zu trainieren, wobei die Identifizierung nützlicher Matching-Abhängigkeiten erlernt wird, welche dann unabhängig von einem bestehenden Goldstandard auf ungesehenen Datensätzen angewendet werden können. Schließlich stellen wir den im Rahmen dieser Arbeit entstehenden Quellcode zur Verfügung, wodurch sowohl die Wiederholbarkeit unserer Forschungsergebnisse als auch die Anwendung unserer Ansätze auf anderen Datensätzen gewährleistet werden soll. T2 - Datenaufbereitung und domänenagnostische Duplikaterkennung KW - duplicate detection KW - data cleaning KW - entity resolution KW - record linkage KW - data preparation KW - data matching KW - address normalization KW - machine learning KW - matching dependencies KW - Adressnormalisierung KW - Datenbereinigung KW - Datenabgleich KW - Datenaufbereitung KW - Duplikaterkennung KW - Entitätsauflösung KW - Maschinelles Lernen KW - Abgleich von Abhängigkeiten KW - Datensatzverknüpfung Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-489131 ER - TY - THES A1 - Papenbrock, Thorsten T1 - Data profiling - efficient discovery of dependencies T1 - Profilerstellung für Daten - Effiziente Entdeckung von Abhängigkeiten N2 - Data profiling is the computer science discipline of analyzing a given dataset for its metadata. The types of metadata range from basic statistics, such as tuple counts, column aggregations, and value distributions, to much more complex structures, in particular inclusion dependencies (INDs), unique column combinations (UCCs), and functional dependencies (FDs). If present, these statistics and structures serve to efficiently store, query, change, and understand the data. Most datasets, however, do not provide their metadata explicitly so that data scientists need to profile them. While basic statistics are relatively easy to calculate, more complex structures present difficult, mostly NP-complete discovery tasks; even with good domain knowledge, it is hardly possible to detect them manually. Therefore, various profiling algorithms have been developed to automate the discovery. None of them, however, can process datasets of typical real-world size, because their resource consumptions and/or execution times exceed effective limits. In this thesis, we propose novel profiling algorithms that automatically discover the three most popular types of complex metadata, namely INDs, UCCs, and FDs, which all describe different kinds of key dependencies. The task is to extract all valid occurrences from a given relational instance. The three algorithms build upon known techniques from related work and complement them with algorithmic paradigms, such as divide & conquer, hybrid search, progressivity, memory sensitivity, parallelization, and additional pruning to greatly improve upon current limitations. Our experiments show that the proposed algorithms are orders of magnitude faster than related work. They are, in particular, now able to process datasets of real-world, i.e., multiple gigabytes size with reasonable memory and time consumption. Due to the importance of data profiling in practice, industry has built various profiling tools to support data scientists in their quest for metadata. These tools provide good support for basic statistics and they are also able to validate individual dependencies, but they lack real discovery features even though some fundamental discovery techniques are known for more than 15 years. To close this gap, we developed Metanome, an extensible profiling platform that incorporates not only our own algorithms but also many further algorithms from other researchers. With Metanome, we make our research accessible to all data scientists and IT-professionals that are tasked with data profiling. Besides the actual metadata discovery, the platform also offers support for the ranking and visualization of metadata result sets. Being able to discover the entire set of syntactically valid metadata naturally introduces the subsequent task of extracting only the semantically meaningful parts. This is challenge, because the complete metadata results are surprisingly large (sometimes larger than the datasets itself) and judging their use case dependent semantic relevance is difficult. To show that the completeness of these metadata sets is extremely valuable for their usage, we finally exemplify the efficient processing and effective assessment of functional dependencies for the use case of schema normalization. N2 - Data Profiling ist eine Disziplin der Informatik, die sich mit der Analyse von Datensätzen auf deren Metadaten beschäftigt. Die verschiedenen Typen von Metadaten reichen von einfachen Statistiken wie Tupelzahlen, Spaltenaggregationen und Wertverteilungen bis hin zu weit komplexeren Strukturen, insbesondere Inklusionsabhängigkeiten (INDs), eindeutige Spaltenkombinationen (UCCs) und funktionale Abhängigkeiten (FDs). Diese Statistiken und Strukturen dienen, sofern vorhanden, dazu die Daten effizient zu speichern, zu lesen, zu ändern und zu verstehen. Die meisten Datensätze stellen ihre Metadaten aber nicht explizit zur Verfügung, so dass Informatiker sie mittels Data Profiling bestimmen müssen. Während einfache Statistiken noch relativ schnell zu berechnen sind, stellen die komplexen Strukturen schwere, zumeist NP-vollständige Entdeckungsaufgaben dar. Es ist daher auch mit gutem Domänenwissen in der Regel nicht möglich sie manuell zu entdecken. Aus diesem Grund wurden verschiedenste Profiling Algorithmen entwickelt, die die Entdeckung automatisieren. Keiner dieser Algorithmen kann allerdings Datensätze von heutzutage typischer Größe verarbeiten, weil entweder der Ressourcenverbrauch oder die Rechenzeit effektive Grenzen überschreiten. In dieser Arbeit stellen wir neuartige Profiling Algorithmen vor, die automatisch die drei populärsten Typen komplexer Metadaten entdecken können, nämlich INDs, UCCs, und FDs, die alle unterschiedliche Formen von Schlüssel-Abhängigkeiten beschreiben. Die Aufgabe dieser Algorithmen ist es alle gültigen Vorkommen der drei Metadaten-Typen aus einer gegebenen relationalen Instanz zu extrahieren. Sie nutzen dazu bekannte Entdeckungstechniken aus verwandten Arbeiten und ergänzen diese um algorithmische Paradigmen wie Teile-und-Herrsche, hybrides Suchen, Progressivität, Speichersensibilität, Parallelisierung und zusätzliche Streichungsregeln. Unsere Experimente zeigen, dass die vorgeschlagenen Algorithmen mit den neuen Techniken nicht nur um Größenordnungen schneller sind als alle verwandten Arbeiten, sie erweitern auch aktuelle Beschränkungen deutlich. Sie können insbesondere nun Datensätze realer Größe, d.h. mehrerer Gigabyte Größe mit vernünftigem Speicher- und Zeitverbrauch verarbeiten. Aufgrund der praktischen Relevanz von Data Profiling hat die Industrie verschiedene Profiling Werkzeuge entwickelt, die Informatiker in ihrer Suche nach Metadaten unterstützen sollen. Diese Werkzeuge bieten eine gute Unterstützung für die Berechnung einfacher Statistiken. Sie sind auch in der Lage einzelne Abhängigkeiten zu validieren, allerdings mangelt es ihnen an Funktionen zur echten Entdeckung von Metadaten, obwohl grundlegende Entdeckungstechniken schon mehr als 15 Jahre bekannt sind. Um diese Lücke zu schließen haben wir Metanome entwickelt, eine erweiterbare Profiling Plattform, die nicht nur unsere eigenen Algorithmen sondern auch viele weitere Algorithmen anderer Forscher integriert. Mit Metanome machen wir unsere Forschungsergebnisse für alle Informatiker und IT-Fachkräfte zugänglich, die ein modernes Data Profiling Werkzeug benötigen. Neben der tatsächlichen Metadaten-Entdeckung bietet die Plattform zusätzlich Unterstützung bei der Bewertung und Visualisierung gefundener Metadaten. Alle syntaktisch korrekten Metadaten effizient finden zu können führt natürlicherweise zur Folgeaufgabe daraus nur die semantisch bedeutsamen Teile zu extrahieren. Das ist eine Herausforderung, weil zum einen die Mengen der gefundenen Metadaten überraschenderweise groß sind (manchmal größer als der untersuchte Datensatz selbst) und zum anderen die Entscheidung über die Anwendungsfall-spezifische semantische Relevanz einzelner Metadaten-Aussagen schwierig ist. Um zu zeigen, dass die Vollständigkeit der Metadaten sehr wertvoll für ihre Nutzung ist, veranschaulichen wir die effiziente Verarbeitung und effektive Bewertung von funktionalen Abhängigkeiten am Anwendungsfall Schema Normalisierung. KW - data profiling KW - functional dependency KW - unique column combination KW - inclusion dependency KW - dependency KW - metanome KW - metadata KW - discovery KW - hybrid KW - divide-and-conquer KW - Profilerstellung für Daten KW - funktionale Abhängigkeit KW - eindeutige Spaltenkombination KW - Inklusionsabhängigkeit KW - Abhängigkeit KW - Metanome KW - Metadaten KW - Entdeckung KW - Hybrid KW - Teile und Herrsche Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-406705 ER - TY - GEN A1 - Bazhenova, Ekaterina A1 - Zerbato, Francesca A1 - Weske, Mathias T1 - Data-Centric Extraction of DMN Decision Models from BPMN Process Models T2 - Business Process Management Workshops N2 - Operational decisions in business processes can be modeled by using the Decision Model and Notation (DMN). The complementary use of DMN for decision modeling and of the Business Process Model and Notation (BPMN) for process design realizes the separation of concerns principle. For supporting separation of concerns during the design phase, it is crucial to understand which aspects of decision-making enclosed in a process model should be captured by a dedicated decision model. Whereas existing work focuses on the extraction of decision models from process control flow, the connection of process-related data and decision models is still unexplored. In this paper, we investigate how process-related data used for making decisions can be represented in process models and we distinguish a set of BPMN patterns capturing such information. Then, we provide a formal mapping of the identified BPMN patterns to corresponding DMN models and apply our approach to a real-world healthcare process. KW - Business process models KW - Process-related data KW - Decision models Y1 - 2018 SN - 978-3-319-74030-0 SN - 978-3-319-74029-4 U6 - https://doi.org/10.1007/978-3-319-74030-0_43 SN - 1865-1348 VL - 308 SP - 542 EP - 555 PB - Springer CY - Berlin ER - TY - THES A1 - Taeumel, Marcel T1 - Data-driven tool construction in exploratory programming environments T1 - Datengetriebener Werkzeugbau in explorativen Programmierumgebungen N2 - This work presents a new design for programming environments that promote the exploration of domain-specific software artifacts and the construction of graphical tools for such program comprehension tasks. In complex software projects, tool building is essential because domain- or task-specific tools can support decision making by representing concerns concisely with low cognitive effort. In contrast, generic tools can only support anticipated scenarios, which usually align with programming language concepts or well-known project domains. However, the creation and modification of interactive tools is expensive because the glue that connects data to graphics is hard to find, change, and test. Even if valuable data is available in a common format and even if promising visualizations could be populated, programmers have to invest many resources to make changes in the programming environment. Consequently, only ideas of predictably high value will be implemented. In the non-graphical, command-line world, the situation looks different and inspiring: programmers can easily build their own tools as shell scripts by configuring and combining filter programs to process data. We propose a new perspective on graphical tools and provide a concept to build and modify such tools with a focus on high quality, low effort, and continuous adaptability. That is, (1) we propose an object-oriented, data-driven, declarative scripting language that reduces the amount of and governs the effects of glue code for view-model specifications, and (2) we propose a scalable UI-design language that promotes short feedback loops in an interactive, graphical environment such as Morphic known from Self or Squeak/Smalltalk systems. We implemented our concept as a tool building environment, which we call VIVIDE, on top of Squeak/Smalltalk and Morphic. We replaced existing code browsing and debugging tools to iterate within our solution more quickly. In several case studies with undergraduate and graduate students, we observed that VIVIDE can be applied to many domains such as live language development, source-code versioning, modular code browsing, and multi-language debugging. Then, we designed a controlled experiment to measure the effect on the time to build tools. Several pilot runs showed that training is crucial and, presumably, takes days or weeks, which implies a need for further research. As a result, programmers as users can directly work with tangible representations of their software artifacts in the VIVIDE environment. Tool builders can write domain-specific scripts to populate views to approach comprehension tasks from different angles. Our novel perspective on graphical tools can inspire the creation of new trade-offs in modularity for both data providers and view designers. N2 - Diese Arbeit schlägt einen neuartigen Entwurf für Programmierumgebungen vor, welche den Umgang mit domänenspezifischen Software-Artefakten erleichtern und die Konstruktion von unterstützenden, grafischen Werkzeugen fördern. Werkzeugbau ist in komplexen Software-Projekten ein essentieller Bestandteil, weil spezifische, auf Domäne und Aufgabe angepasste, Werkzeuge relevante Themen und Konzepte klar darstellen und somit effizient zur Entscheidungsfindung beitragen können. Im Gegensatz dazu sind vorhandene, traditionelle Werkzeuge nur an allgemeinen, wiederkehrenden Anforderungen ausgerichtet, welche im Spezialfall Gedankengänge nur unzureichend abbilden können. Leider sind das Erstellen und Anpassen von interaktiven Werkzeugen teuer, weil die Beschreibungen zwischen Information und Repräsentation nur schwer auffindbar, änderbar und prüfbar sind. Selbst wenn relevante Daten verfügbar und vielversprechende Visualisierungen konfigurierbar sind, müssten Programmierer viele Ressourcen für das Verändern ihrer Programmierumgeben investieren. Folglich können nur Ideen von hohem Wert umgesetzt werden, um diese Kosten zu rechtfertigen. Dabei sieht die Situation in der textuellen Welt der Kommandozeile sehr vielversprechend aus. Dort können Programmierer einfach ihre Werkzeuge in Form von Skripten anpassen und kleine Filterprogramme kombinieren, um Daten zu verarbeiten. Wir stellen eine neuartige Perspektive auf grafische Werkzeuge vor und vermitteln dafür ein Konzept, um diese Werkzeuge mit geringem Aufwand und in hoher Qualität zu konstruieren. Im Detail beinhaltet das, erstens, eine objekt-orientierte, daten-getriebene, deklarative Skriptsprache, um die Programmierschnittstelle zwischen Information und Repräsentation zu vereinfachen. Zweitens ist dies eine skalierbare Entwurfssprache für Nutzerschnitt-stellen, welche kurze Feedback-Schleifen und Interaktivität kombiniert, wie es in den Umgebungen Self oder Squeak/Smalltalk typisch ist. Wir haben unser Konzept in Form einer neuartigen Umgebung für Werkzeugbau mit Hilfe von Squeak/Smalltalk und Morphic umgesetzt. Die Umgebung trägt den Namen VIVIDE. Damit konnten wir die bestehenden Werkzeuge von Squeak für Quelltextexploration und ausführung ersetzen, um unsere Lösung kontinuierlich zu verbessern. In mehreren Fallstudien mit Studenten konnten wir beobachten, dass sich VIVIDE in vielen Domänen anwenden lässt: interaktive Entwicklung von Programmiersprachen, modulare Versionierung und Exploration von Quelltext und Fehleranalyse von mehrsprachigen Systemen. Mit Blick auf zukünftige Forschung haben wir ebenfalls ein kontrolliertes Experiment entworfen. Nach einigen Testläufen stellte sich die Trainingsphase von VIVIDE als größte, und somit offene, Herausforderung heraus. Im Ergebnis sind wir davon überzeugt, dass Programmierer in VIVIDE direkt mit greifbaren, interaktiven Darstellungen relevanter Software-Artefakte arbeiten können. Im Rahmen des Werkzeugbaus können Programmierer kompakte, angepasste Skripte schreiben, die Visualisierungen konfigurieren, um Programmieraufgaben spezifisch aus mehreren Blickwinkeln zu betrachten. Unsere neuartige Perspektive auf grafische Werkzeuge kann damit sowohl das Bereitstellen von Informationen, als auch den Entwurf interaktiver Grafik positiv beeinflussen. KW - programming KW - tool building KW - user interaction KW - exploration KW - liveness KW - immediacy KW - direct manipulation KW - scripting languages KW - Squeak/Smalltalk KW - Programmieren KW - Werkzeugbau KW - Nutzerinteraktion KW - Exploration KW - Lebendigkeit KW - Direkte Manipulation KW - Skriptsprachen KW - Squeak/Smalltalk Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-444289 ER - TY - JOUR A1 - Schlosser, Rainer A1 - Boissier, Martin T1 - Dealing with the dimensionality curse in dynamic pricing competition BT - Using frequent repricing to compensate imperfect market anticipations JF - Computers & Operations Research N2 - Most sales applications are characterized by competition and limited demand information. For successful pricing strategies, frequent price adjustments as well as anticipation of market dynamics are crucial. Both effects are challenging as competitive markets are complex and computations of optimized pricing adjustments can be time-consuming. We analyze stochastic dynamic pricing models under oligopoly competition for the sale of perishable goods. To circumvent the curse of dimensionality, we propose a heuristic approach to efficiently compute price adjustments. To demonstrate our strategy’s applicability even if the number of competitors is large and their strategies are unknown, we consider different competitive settings in which competitors frequently and strategically adjust their prices. For all settings, we verify that our heuristic strategy yields promising results. We compare the performance of our heuristic against upper bounds, which are obtained by optimal strategies that take advantage of perfect price anticipations. We find that price adjustment frequencies can have a larger impact on expected profits than price anticipations. Finally, our approach has been applied on Amazon for the sale of used books. We have used a seller’s historical market data to calibrate our model. Sales results show that our data-driven strategy outperforms the rule-based strategy of an experienced seller by a profit increase of more than 20%. KW - Dynamic pricing KW - Oligopoly competition KW - Dynamic programming KW - Data-driven strategies KW - E-commerce Y1 - 2018 U6 - https://doi.org/10.1016/j.cor.2018.07.011 SN - 0305-0548 SN - 1873-765X VL - 100 SP - 26 EP - 42 PB - Elsevier CY - Oxford ER - TY - BOOK A1 - Bartz, Christian A1 - Krestel, Ralf T1 - Deep learning for computer vision in the art domain BT - proceedings of the master seminar on practical introduction to deep learning for computer vision, HPI WS 20/21 N2 - In recent years, computer vision algorithms based on machine learning have seen rapid development. In the past, research mostly focused on solving computer vision problems such as image classification or object detection on images displaying natural scenes. Nowadays other fields such as the field of cultural heritage, where an abundance of data is available, also get into the focus of research. In the line of current research endeavours, we collaborated with the Getty Research Institute which provided us with a challenging dataset, containing images of paintings and drawings. In this technical report, we present the results of the seminar "Deep Learning for Computer Vision". In this seminar, students of the Hasso Plattner Institute evaluated state-of-the-art approaches for image classification, object detection and image recognition on the dataset of the Getty Research Institute. The main challenge when applying modern computer vision methods to the available data is the availability of annotated training data, as the dataset provided by the Getty Research Institute does not contain a sufficient amount of annotated samples for the training of deep neural networks. However, throughout the report we show that it is possible to achieve satisfying to very good results, when using further publicly available datasets, such as the WikiArt dataset, for the training of machine learning models. N2 - Methoden zur Anwendung von maschinellem Lernen für das maschinelle Sehen haben sich in den letzten Jahren stark weiterentwickelt. Dabei konzentrierte sich die Forschung hauptsächlich auf die Lösung von Problemen im Bereich der Bildklassifizierung, oder der Objekterkennung aus Bildern mit natürlichen Motiven. Mehr und mehr kommen zusätzlich auch andere Inhaltsbereiche, vor allem aus dem kulturellen Umfeld in den Fokus der Forschung. Kulturforschungsinstitute, wie das Getty Research Institute, besitzen eine Vielzahl von digitalisierten Dokumenten, die bisher noch nicht analysiert wurden. Im Rahmen einer Zusammenarbeit, überließ das Getty Research Institute uns einen Datensatz, bestehend aus Photos von Kunstwerken. In diesem technischen Bericht präsentieren wir die Ergebnisse des Masterseminars "Deep Learning for Computer Vision", in dem Studierende des Hasso-Plattner-Instituts den Stand der Kunst, bei der Anwendung von Bildklassifizierungs, Objekterkennungs und Image Retrieval Algorithmen evaluierten. Eine besondere Schwierigkeit war, dass es nicht möglich ist bestehende Verfahren direkt auf dem Datensatz anzuwenden, da keine, bzw. kaum Annotationen für das Training von Machine Learning Modellen verfügbar sind. In den einzelnen Teilen des Berichts zeigen wir jedoch, dass es möglich ist unter Zuhilfenahme von weiteren öffentlich verfügbaren Datensätzen, wie dem WikiArt Datensatz, zufriedenstellende bis sehr gute Ergebnisse für die einzelnen Analyseaufgaben zu erreichen. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 139 KW - computer vision KW - cultural heritage KW - art analysis KW - maschinelles Sehen KW - kulturelles Erbe KW - Kunstanalyse Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-512906 SN - 978-3-86956-514-9 SN - 1613-5652 SN - 2191-1665 IS - 139 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - THES A1 - Yang, Haojin T1 - Deep representation learning for multimedia data analysis Y1 - 2019 ER - TY - THES A1 - Rezaei, Mina T1 - Deep representation learning from imbalanced medical imaging N2 - Medical imaging plays an important role in disease diagnosis, treatment planning, and clinical monitoring. One of the major challenges in medical image analysis is imbalanced training data, in which the class of interest is much rarer than the other classes. Canonical machine learning algorithms suppose that the number of samples from different classes in the training dataset is roughly similar or balance. Training a machine learning model on an imbalanced dataset can introduce unique challenges to the learning problem. A model learned from imbalanced training data is biased towards the high-frequency samples. The predicted results of such networks have low sensitivity and high precision. In medical applications, the cost of misclassification of the minority class could be more than the cost of misclassification of the majority class. For example, the risk of not detecting a tumor could be much higher than referring to a healthy subject to a doctor. The current Ph.D. thesis introduces several deep learning-based approaches for handling class imbalanced problems for learning multi-task such as disease classification and semantic segmentation. At the data-level, the objective is to balance the data distribution through re-sampling the data space: we propose novel approaches to correct internal bias towards fewer frequency samples. These approaches include patient-wise batch sampling, complimentary labels, supervised and unsupervised minority oversampling using generative adversarial networks for all. On the other hand, at algorithm-level, we modify the learning algorithm to alleviate the bias towards majority classes. In this regard, we propose different generative adversarial networks for cost-sensitive learning, ensemble learning, and mutual learning to deal with highly imbalanced imaging data. We show evidence that the proposed approaches are applicable to different types of medical images of varied sizes on different applications of routine clinical tasks, such as disease classification and semantic segmentation. Our various implemented algorithms have shown outstanding results on different medical imaging challenges. N2 - Medizinische Bildanalyse spielt eine wichtige Rolle bei der Diagnose von Krankheiten, der Behandlungsplanung, und der klinischen Überwachung. Eines der großen Probleme in der medizinischen Bildanalyse ist das Vorhandensein von nicht ausbalancierten Trainingsdaten, bei denen die Anzahl der Datenpunkte der Zielklasse in der Unterzahl ist. Die Aussagen eines Modells, welches auf einem unbalancierten Datensatz trainiert wurde, tendieren dazu Datenpunkte in die Klasse mit der Mehrzahl an Trainingsdaten einzuordnen. Die Aussagen eines solchen Modells haben eine geringe Sensitivität aber hohe Genauigkeit. Im medizinischen Anwendungsbereich kann die Einordnung eines Datenpunktes in eine falsche Klasse Schwerwiegende Ergebnisse mit sich bringen. In die Nichterkennung eines Tumors Beispielsweise brigt ein viel höheres Risiko für einen Patienten, als wenn ein gesunder Patient zum Artz geschickt wird. Das Problem des Lernens unter Nutzung von nicht ausbalancierten Trainingsdaten wird erst seit Kurzem bei der Klassifizierung von Krankheiten, der Entdeckung von Tumoren und beider Segmentierung von Tumoren untersucht. In der Literatur wird hier zwischen zwei verschiedenen Ansätzen unterschieden: datenbasierte und algorithmische Ansätze. Die vorliegende Arbeit behandelt das Lernen unter Nutzung von unbalancierten medizinischen Bilddatensätzen mittels datenbasierter und algorithmischer Ansätze. Bei den datenbasierten Ansätzen ist es unser Ziel, die Datenverteilung durch gezieltes Nutzen der vorliegenden Datenbasis auszubalancieren. Dazu schlagen wir neuartige Ansätze vor, um eine ausgeglichene Einordnung der Daten aus seltenen Klassen vornehmen zu können. Diese Ansätze sind unter anderem synthesize minority class sampling, patient-wise batch normalization, und die Erstellung von komplementären Labels unter Nutzung von generative adversarial networks. Auf der Seite der algorithmischen Ansätze verändern wir den Trainingsalgorithmus, um die Tendenz in Richtung der Klasse mit der Mehrzahl an Trainingsdaten zu verringern. Dafür schlagen wir verschiedene Algorithmen im Bereich des kostenintensiven Lernens, Ensemble-Lernens und des gemeinsamen Lernens vor, um mit stark unbalancierten Trainingsdaten umgehen zu können. Wir zeigen, dass unsere vorgeschlagenen Ansätze für verschiedenste Typen von medizinischen Bildern, mit variierender Größe, auf verschiedene Anwendungen im klinischen Alltag, z. B. Krankheitsklassifizierung, oder semantische Segmentierung, anwendbar sind. Weiterhin haben unsere Algorithmen hervorragende Ergebnisse bei unterschiedlichen Wettbewerben zur medizinischen Bildanalyse gezeigt. KW - machine learning KW - deep learning KW - computer vision KW - imbalanced learning KW - medical image analysis KW - Maschinenlernen KW - tiefes Lernen KW - unbalancierter Datensatz KW - Computervision KW - medizinische Bildanalyse Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-442759 ER - TY - JOUR A1 - Ziegler, Joceline A1 - Pfitzner, Bjarne A1 - Schulz, Heinrich A1 - Saalbach, Axel A1 - Arnrich, Bert T1 - Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data JF - Sensors N2 - Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training. KW - federated learning KW - privacy and security KW - privacy attack KW - X-ray Y1 - 2022 U6 - https://doi.org/10.3390/s22145195 SN - 1424-8220 VL - 22 PB - MDPI CY - Basel, Schweiz ET - 14 ER - TY - GEN A1 - Ziegler, Joceline A1 - Pfitzner, Bjarne A1 - Schulz, Heinrich A1 - Saalbach, Axel A1 - Arnrich, Bert T1 - Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 14 KW - federated learning KW - privacy and security KW - privacy attack KW - X-ray Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-581322 IS - 14 ER - TY - JOUR A1 - Krentz, Konrad-Felix A1 - Meinel, Christoph T1 - Denial-of-sleep defenses for IEEE 802.15.4 coordinated sampled listening (CSL) JF - Computer Networks N2 - Coordinated sampled listening (CSL) is a standardized medium access control protocol for IEEE 80215.4 networks. Unfortunately, CSL comes without any protection against so-called denial-of-sleep attacks. Such attacks deprive energy-constrained devices of entering low-power sleep modes, thereby draining their charge. Repercussions of denial-of-sleep attacks include long outages, violated quality-of-service guarantees, and reduced customer satisfaction. However, while CSL has no built-in denial-of-sleep defenses, there already exist denial-of-sleep defenses for a predecessor of CSL, namely ContikiMAC. In this paper, we make two main contributions. First, motivated by the fact that CSL has many advantages over ContikiMAC, we tailor the existing denial-of-sleep defenses for ContikiMAC to CSL. Second, we propose several security enhancements to these existing denial-of-sleep defenses. In effect, our denial-of-sleep defenses for CSL mitigate denial-of-sleep attacks significantly better, as well as protect against a larger range of denial-of-sleep attacks than the existing denial-of-sleep defenses for ContikiMAC. We show the soundness of our denial-of-sleep defenses for CSL both analytically, as well as empirically using a whole new implementation of CSL. (C) 2018 Elsevier B.V. All rights reserved. KW - Internet of things KW - Link layer security KW - MAC security KW - Denial of sleep Y1 - 2018 U6 - https://doi.org/10.1016/j.comnet.2018.10.021 SN - 1389-1286 SN - 1872-7069 VL - 148 SP - 60 EP - 71 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Giannatelli, Ada A1 - Tomasini, Alessandra ED - Meinel, Christoph ED - Schweiger, Stefanie ED - Staubitz, Thomas ED - Conrad, Robert ED - Alario Hoyos, Carlos ED - Ebner, Martin ED - Sancassani, Susanna ED - Żur, Agnieszka ED - Friedl, Christian ED - Halawa, Sherif ED - Gamage, Dilrukshi ED - Scott, Jeffrey ED - Kristine Jonson Carlon, May ED - Deville, Yves ED - Gaebel, Michael ED - Delgado Kloos, Carlos ED - von Schmieden, Karen T1 - Descriptors and EU Standards to support the recognition of MOOCs JF - EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash? N2 - Digital technologies have enabled a variety of learning offers that opened new challenges in terms of recognition of formal, informal and non-formal learning, such as MOOCs. This paper focuses on how providing relevant data to describe a MOOC is conducive to increase the transparency of information and, ultimately, the flexibility of European higher education. The EU-funded project ECCOE took up these challenges and developed a solution by identifying the most relevant descriptors of a learning opportunity with a view to supporting a European system for micro-credentials. Descriptors indicate the specific properties of a learning opportunity according to European standards. They can provide a recognition framework also for small volumes of learning (micro-credentials) to support the integration of non-formal learning (MOOCs) into formal learning (e.g. institutional university courses) and to tackle skills shortage, upskilling and reskilling by acquiring relevant competencies. The focus on learning outcomes can facilitate the recognition of skills and competences of students and enhance both virtual and physical mobility and employability. This paper presents two contexts where ECCOE descriptors have been adopted: the Politecnico di Milano MOOC platform (Polimi Open Knowledge – POK), which is using these descriptors as the standard information to document the features of its learning opportunities, and the EU-funded Uforest project on urban forestry, which developed a blended training program for students of partner universities whose MOOCs used the ECCOE descriptors. Practice with ECCOE descriptors shows how they can be used not only to detail MOOC features, but also as a compass to design the learning offer. In addition, some rules of thumb can be derived and applied when using specific descriptors. KW - Digitale Bildung KW - Kursdesign KW - MOOC KW - Micro Degree KW - Online-Lehre KW - Onlinekurs KW - Onlinekurs-Produktion KW - digital education KW - e-learning KW - micro degree KW - micro-credential KW - online course creation KW - online course design KW - online teaching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-623967 SP - 133 EP - 146 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Bender, Benedict A1 - Grum, Marcus A1 - Gronau, Norbert A1 - Alfa, Attahiru A1 - Maharaj, B. T. T1 - Design of a worldwide simulation system for distributed cyber-physical production networks T2 - 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) N2 - Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example. KW - production networks KW - geographical distribution KW - task realization strategies KW - Industry 4.0 KW - simulation KW - evaluation Y1 - 2019 SN - 978-1-7281-3401-7 SN - 978-1-7281-3402-4 U6 - https://doi.org/10.1109/ICE.2019.8792609 SN - 2334-315X PB - IEEE CY - New York ER - TY - GEN A1 - Pufahl, Luise A1 - Wong, Tsun Yin A1 - Weske, Mathias T1 - Design of an extensible BPMN process simulator T2 - Business Process Management Workshops (BPM 2017) N2 - Business process simulation is an important means for quantitative analysis of a business process and to compare different process alternatives. With the Business Process Model and Notation (BPMN) being the state-of-the-art language for the graphical representation of business processes, many existing process simulators support already the simulation of BPMN diagrams. However, they do not provide well-defined interfaces to integrate new concepts in the simulation environment. In this work, we present the design and architecture of a proof-of-concept implementation of an open and extensible BPMN process simulator. It also supports the simulation of multiple BPMN processes at a time and relies on the building blocks of the well-founded discrete event simulation. The extensibility is assured by a plug-in concept. Its feasibility is demonstrated by extensions supporting new BPMN concepts, such as the simulation of business rule activities referencing decision models and batch activities. KW - Business process simulation KW - Extensibility KW - BPMN Y1 - 2018 SN - 978-3-319-74030-0 SN - 978-3-319-74029-4 U6 - https://doi.org/10.1007/978-3-319-74030-0_62 SN - 1865-1348 VL - 308 SP - 782 EP - 795 PB - Springer CY - Berlin ER - TY - THES A1 - Traifeh, Hanadi T1 - Design Thinking in the Arab world T1 - Design Thinking in der Arabischen Welt BT - perspectives, challenges and opportunities BT - Perspektiven, Herausforderungen und Potentiale N2 - Design Thinking is a human-centered approach to innovation that has become increasingly popular globally over the last decade. While the spread of Design Thinking is well understood and documented in the Western cultural contexts, particularly in Europe and the US due to the popularity of the Stanford-Potsdam Design Thinking education model, this is not the case when it comes to non-Western cultural contexts. This thesis fills a gap identified in the literature regarding how Design Thinking emerged, was perceived, adopted, and practiced in the Arab world. The culture in that part of the world differs from that of the Western context, which impacts the mindset of people and how they interact with Design Thinking tools and methods. A mixed-methods research approach was followed in which both quantitative and qualitative methods were employed. First, two methods were used in the quantitative phase: a social media analysis using Twitter as a source of data, and an online questionnaire. The results and analysis of the quantitative data informed the design of the qualitative phase in which two methods were employed: ten semi-structured interviews, and participant observation of seven Design Thinking training events. According to the analyzed data, the Arab world appears to have had an early, though relatively weak, and slow, adoption of Design Thinking since 2006. Increasing adoption, however, has been witnessed over the last decade, especially in Saudi Arabia, the United Arab Emirates and Egypt. The results also show that despite its limited spread, Design Thinking has been practiced the most in education, information technology and communication, administrative services, and the non-profit sectors. The way it is being practiced, though, is not fully aligned with how it is being practiced and taught in the US and Europe, as most people in the region do not necessarily believe in all mindset attributes introduced by the Stanford-Potsdam tradition. Practitioners in the Arab world also seem to shy away from the 'wild side' of Design Thinking in particular, and do not fully appreciate the connection between art-design, and science-engineering. This questions the role of the educational institutions in the region since -according to the findings- they appear to be leading the movement in promoting and developing Design Thinking in the Arab world. Nonetheless, it is notable that people seem to be aware of the positive impact of applying Design Thinking in the region, and its potential to bring meaningful transformation. However, they also seem to be concerned about the current cultural, social, political, and economic challenges that may challenge this transformation. Therefore, they call for more awareness and demand to create Arabic, culturally appropriate programs to respond to the local needs. On another note, the lack of Arabic content and local case studies on Design Thinking were identified by several interviewees and were also confirmed by the participant observation as major challenges that are slowing down the spread of Design Thinking or sometimes hampering capacity building in the region. Other challenges that were revealed by the study are: changing the mindset of people, the lack of dedicated Design Thinking spaces, and the need for clear instructions on how to apply Design Thinking methods and activities. The concept of time and how Arabs deal with it, gender management during trainings, and hierarchy and power dynamics among training participants are also among the identified challenges. Another key finding revealed by the study is the confirmation of التفكير التصميمي as the Arabic term to be most widely adopted in the region to refer to Design Thinking, since four other Arabic terms were found to be associated with Design Thinking. Based on the findings of the study, the thesis concludes by presenting a list of recommendations on how to overcome the mentioned challenges and what factors should be considered when designing and implementing culturally-customized Design Thinking training in the Arab region. N2 - Design Thinking ist ein nutzerzentrierter Innovationsansatz, der in den letzten zehn Jahren weltweit an Bekanntheit gewonnen hat. Während die Verbreitung von Design Thinking im westlichen Kulturkreis – insbesondere in Europa und den USA – aufgrund der Bedeutung des Stanford-Potsdam Design Thinking-Ausbildungsmodells gut verstanden und dokumentiert ist, ist dies nicht der Fall, wenn es sich um nicht-westliche Kulturkreise handelt. Diese Arbeit schließt eine Lücke in der Literatur darüber, wie Design Thinking in der arabischen Welt entstanden ist, wahrgenommen, angenommen und praktiziert wurde. Die vorhandenen kulturellen Unterschiede zwischen der westlichen und der arabischen Welt wirken sich auch auf die Denkweise der Menschen aus, unddarauf, wie sie mit Design Thinking-Tools und -Methoden umgehen. Es wurde ein ‚Mixed Methods‘-Forschungsansatz verfolgt, d.h. sowohl quantitative als auch qualitative Methoden wurden eingesetzt. In der quantitativen Phase kamen zunächst zwei Methoden zum Einsatz: eine Social-Media-Analyse mit Twitter als Datenquelle und ein Online-Fragebogen. Die Ergebnisse und die Analyse der quantitativen Daten bildeten die Grundlage für die Gestaltung der qualitativen Phase, in der zwei Methoden angewendet wurden: zehn halbstrukturierte Interviews und die teilnehmende Beobachtung von sieben Design Thinking-Trainings. Den analysierten Daten zufolge scheint es in der arabischen Welt seit 2006 eine frühe, wenn auch relativ schwache und langsame Einführung von Design Thinking gegeben zu haben. In den letzten zehn Jahren ist jedoch eine zunehmende Akzeptanz zu beobachten, insbesondere in Saudi-Arabien, den Vereinigten Arabischen Emiraten und Ägypten. Die Ergebnisse zeigen auch, dass Design Thinking trotz seiner begrenzten Verbreitung am häufigsten im Bildungswesen, in der Informationstechnologie und Kommunikation, in der Verwaltung und im Non-Profit-Sektor angewandt wird. Die Art und Weise, wie Design Thinking praktiziert wird, stimmt jedoch nicht vollständig mit der Art und Weise überein, wie es in den USA und Europa praktiziert und gelehrt wird, da die meisten Menschen in der Region nicht unbedingt an alle Denkattribute glauben, die im Stanford-Potsdam-Modell eingeführt wurden. Die Praktiker in der arabischen Welt scheinen auch vor der "wilden Seite" des Design Thinking zurückzuschrecken und die Verbindung zwischen Kunst und Design auf der einen sowie Wissenschaft und Technik auf der anderen Seite nicht vollumfänglich zu schätzen. Dies wirft die Frage nach der Rolle von Bildungseinrichtungen in der Region auf, da sie - den Ergebnissen zufolge - die Bewegung zur Förderung und Entwicklung von Design Thinking in der arabischen Welt anzuführen scheinen. Nichtsdestotrotz ist es bemerkenswert, dass sich die Menschen der positiven Auswirkungen der Anwendung von Design Thinking in der Region und seines Potenzials, sinnvolle Veränderungen zu bewirken, bewusst zu sein scheinen. Sie scheinen jedoch auch besorgt zu sein über die aktuellen kulturellen, sozialen, politischen und wirtschaftlichen Herausforderungen, die diese Transformation in Frage stellen könnten. Daher fordern sie eine stärkere Sensibilisierung und die Schaffung von arabischen, kulturell angemessenen Programmen, um auf die lokalen Bedürfnisse einzugehen. Auch das Fehlen arabischer Inhalte und lokaler Fallstudien zu Design Thinking wurde von mehreren Befragten genannt und durch die teilnehmende Beobachtung bestätigt, da dies die Verbreitung von Design Thinking verlangsamt oder den Aufbau von Kapazitäten in der Region behindert. Weitere Herausforderungen, die sich aus der Studie ergaben, sind: die Veränderung des Mindsets der Menschen, das Fehlen spezieller Design-Thinking-Räume und der Bedarf an klaren Anweisungen zur Anwendung von Design-Thinking-Methoden und -Aktivitäten. Das Konzept von Zeit und der Umgang der arabischen Welt damit, Gender-Management während der Schulungen sowie Hierarchie und Machtdynamik unter den Schulungsteilnehmern gehören ebenfalls zu den identifizierten Herausforderungen. Ein weiteres wichtiges Ergebnis der Studie ist die Bestätigung von التفكير التصميمي als dem in der Region am weitesten verbreiteten arabischen Begriff für Design Thinking, da vier weitere arabische Begriffe mit Design Thinking in Verbindung gebracht werden konnten. Basierend auf den Ergebnissen der Studie schließt die Arbeit mit einer Liste von Empfehlungen, wie die genannten Herausforderungen überwunden werden können und welche Faktoren bei der Entwicklung und Implementierung von kulturell angepassten Design Thinking-Trainings in der arabischen Welt berücksichtigt werden sollten. KW - Design Thinking KW - human-centered design KW - the Arab world KW - emergence KW - adoption KW - implementation KW - culture KW - Design Thinking KW - Annahme KW - Kultur KW - Entstehung KW - menschenzentriertes Design KW - Implementierung KW - die arabische Welt Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-598911 ER - TY - BOOK A1 - Gerken, Stefanie A1 - Uebernickel, Falk A1 - de Paula, Danielly T1 - Design Thinking: a Global Study on Implementation Practices in Organizations T1 - Design Thinking: eine globale Studie über Implementierungspraktiken in Organisationen BT - Past - Present - Future BT - Vergangenheit - Gegenwart - Zukunft N2 - These days design thinking is no longer a “new approach”. Among practitioners, as well as academics, interest in the topic has gathered pace over the last two decades. However, opinions are divided over the longevity of the phenomenon: whether design thinking is merely “old wine in new bottles,” a passing trend, or still evolving as it is being spread to an increasing number of organizations and industries. Despite its growing relevance and the diffusion of design thinking, knowledge on the actual status quo in organizations remains scarce. With a new study, the research team of Prof. Uebernickel and Stefanie Gerken investigates temporal developments and changes in design thinking practices in organizations over the past six years comparing the results of the 2015 “Parts without a whole” study with current practices and future developments. Companies of all sizes and from different parts of the world participated in the survey. The findings from qualitative interviews with experts, i.e., people who have years of knowledge with design thinking, were cross-checked with the results from an exploratory analysis of the survey data. This analysis uncovers significant variances and similarities in how design thinking is interpreted and applied in businesses. N2 - Heutzutage ist Design Thinking kein "neuer Ansatz" mehr. Unter Praktikern und Akademikern hat das Interesse an diesem Thema in den letzten zwei Jahrzehnten stark zugenommen. Die Meinungen sind jedoch geteilt, ob Design Thinking lediglich "alter Wein in neuen Schläuchen" ist, ein vorübergehender Trend, oder ein sich weiterentwickelndes Phänomen, welches in immer mehr Organisationen und Branchen Fuß fast. Trotz der wachsenden Relevanz und Verbreitung von Design Thinking ist das Wissen über den tatsächlichen Status quo in Organisationen nach wie vor spärlich. Mit einer neuen Studie untersucht das Forschungsteam von Prof. Uebernickel, Stefanie Gerken und Dr. Danielly de Paula die zeitlichen Entwicklungen und Veränderungen von Design Thinking Praktiken in Organisationen über die letzten sechs Jahre und vergleicht die Ergebnisse der Studie "Parts without a whole" aus dem Jahr 2015 mit aktuellen Praktiken und perspektivischen Entwicklungen. An der Studie haben Unternehmen aller Größen und aus verschiedenen Teilen der Welt teilgenommen. Um dem komplexen Untersuchungsgegenstand gerecht zu werden, wurde eine Mixed-Method-Ansatz gewählt: Die Erkenntnisse aus qualitativen Experteninterviews, d.h. Personen, die sich seit Jahren mit dem Thema Design Thinking in der Praxis beschäftigen, wurden mit den Ergebnissen einer quantitativen Analyse von Umfragedaten abgeglichen. Die vorliegende Studie erörtert signifikante Unterschiede und Gemeinsamkeiten bei der Interpretation und Anwendung von Design Thinking in Unternehmen. KW - Design Thinking KW - Agile KW - Implementation in Organizations KW - life-centered KW - human-centered KW - Innovation KW - Behavior change KW - Problem Solving KW - Creative KW - Solution Space KW - Process KW - Mindset KW - Tools KW - Wicked Problems KW - VUCA-World KW - Ambiguity KW - Interdisciplinary Teams KW - Multidisciplinary Teams KW - Impact KW - Measurement KW - Ideation KW - Agilität KW - agil KW - Ambiguität KW - Verhaltensänderung KW - Kreativität KW - Design Thinking KW - Ideenfindung KW - Auswirkungen KW - Implementierung in Organisationen KW - Innovation KW - interdisziplinäre Teams KW - Messung KW - Denkweise KW - multidisziplinäre Teams KW - Problemlösung KW - Prozess KW - Lösungsraum KW - Werkzeuge KW - Aktivitäten KW - verzwickte Probleme KW - menschenzentriert KW - lebenszentriert KW - VUCA-World Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-534668 SN - 978-3-86956-525-5 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - THES A1 - Santuber, Joaquin T1 - Designing for digital justice T1 - Designing for Digital Justice T1 - Diseñar para la justicia digital BT - an entanglement of people, law, and technologies in Chilean courts BT - eine Verflechtung von Menschen, Recht und Technologien in chilenischen Gerichten BT - una maraña de personas, leyes y tecnologías en los tribunales chilenos N2 - At the beginning of 2020, with COVID-19, courts of justice worldwide had to move online to continue providing judicial service. Digital technologies materialized the court practices in ways unthinkable shortly before the pandemic creating resonances with judicial and legal regulation, as well as frictions. A better understanding of the dynamics at play in the digitalization of courts is paramount for designing justice systems that serve their users better, ensure fair and timely dispute resolutions, and foster access to justice. Building on three major bodies of literature —e-justice, digitalization and organization studies, and design research— Designing for Digital Justice takes a nuanced approach to account for human and more-than-human agencies. Using a qualitative approach, I have studied in depth the digitalization of Chilean courts during the pandemic, specifically between April 2020 and September 2022. Leveraging a comprehensive source of primary and secondary data, I traced back the genealogy of the novel materializations of courts’ practices structured by the possibilities offered by digital technologies. In five (5) cases studies, I show in detail how the courts got to 1) work remotely, 2) host hearings via videoconference, 3) engage with users via social media (i.e., Facebook and Chat Messenger), 4) broadcast a show with judges answering questions from users via Facebook Live, and 5) record, stream, and upload judicial hearings to YouTube to fulfil the publicity requirement of criminal hearings. The digitalization of courts during the pandemic is characterized by a suspended normativity, which makes innovation possible yet presents risks. While digital technologies enabled the judiciary to provide services continuously, they also created the risk of displacing traditional judicial and legal regulation. Contributing to liminal innovation and digitalization research, Designing for Digital Justice theorizes four phases: 1) the pre-digitalization phase resulting in the development of regulation, 2) the hotspot of digitalization resulting in the extension of regulation, 3) the digital innovation redeveloping regulation (moving to a new, preliminary phase), and 4) the permanence of temporal practices displacing regulation. Contributing to design research Designing for Digital Justice provides new possibilities for innovation in the courts, focusing at different levels to better address tensions generated by digitalization. Fellow researchers will find in these pages a sound theoretical advancement at the intersection of digitalization and justice with novel methodological references. Practitioners will benefit from the actionable governance framework Designing for Digital Justice Model, which provides three fields of possibilities for action to design better justice systems. Only by taking into account digital, legal, and social factors can we design better systems that promote access to justice, the rule of law, and, ultimately social peace. N2 - Durch COVID-19 mussten zu Beginn des Jahres 2020 die Gerichte weltweit, um ihren Dienst fortzusetzen, Onlinekommunikation und digitale Technologien nutzen. Die digitalen Technologien haben die Gerichtspraktiken in einer Weise verändert, die kurz vor der Pandemie noch undenkbar war, was zu Resonanzen mit der Rechtsprechung und der gesetzlichen Regelung sowie zu Reibungen führte. Ein besseres Verständnis der Dynamik, die bei der Digitalisierung von Gerichten im Spiel ist, ist von entscheidender Bedeutung für die Gestaltung von Justizsystemen, die ihren Nutzern besser dienen, faire und zeitnahe Streitbeilegung gewährleisten und den Zugang zur Justiz und zur Rechtsstaatlichkeit fördern. Aufbauend auf den drei großen Themenkomplexen E-Justiz, Digitalisierung und Organisationen sowie Designforschung verfolgt „Designing for Digital Justice“ einen nuancierten Ansatz, um menschliche und nicht-menschliche Akteure zu berücksichtigen. Mit Hilfe eines qualitativen Forschungsansatzes habe ich die Digitalisierung der chilenischen Gerichte während der Pandemie, insbesondere im Zeitraum von April 2020 und September 2022, eingehend untersucht. Auf der Grundlage einer umfassenden Quelle von Primär- und Sekundärdaten habe ich die Genealogie der neuartigen Materialisierung von Gerichtspraktiken zurückverfolgt, die durch die Möglichkeiten der digitalen Technologien strukturiert wurden. In fünf (5) Fallstudien zeige ich im Detail, wie die Gerichte 1) aus der Ferne arbeiten, 2) Anhörungen per Videokonferenz abhalten, 3) mit Nutzern über soziale Medien (beispielsweise Facebook und Chat Messenger) in Kontakt treten, 4) eine Sendung mit Richtern, die Fragen von Nutzern beantworten, über Facebook Live ausstrahlen und 5) Gerichtsverhandlungen aufzeichnen, streamen und auf YouTube hochladen, um die Anforderungen an die Öffentlichkeit von Strafverhandlungen zu erfüllen. Hierbei zeigt sich, dass digitale Technologien der Justiz zwar eine kontinuierliche Bereitstellung von Dienstleistungen ermöglichten. Sie bergen aber auch die Gefahr, dass sie die traditionelle gerichtliche und rechtliche Regulierung verdrängen. Als Beitrag zum Forschungsstrom zu „Liminal Innovation“ und Digitalisierung theoretisiert „Designing for Digital Justice“ vier Phasen: 1) Vor-Digitalisierung, die zur Entwicklung von Regulierung führt, 2) der Hotspot der Digitalisierung, der zur Ausweitung der Regulierung führt, 3) digitale Innovation, die die Regulierung neu entwickelt (Übergang zu einer neuen, provisorischen Phase) und 4) die Permanenz der temporären Praktiken, die die Regulierung verdrängt. Als Beitrag zur Designforschung bietet „Designing for Digital Justice“ neue Möglichkeiten für die Gestaltung von Justizsystemen, indem es Spannungen und Interventionsebenen miteinander verbindet. Forscherkolleg*innen finden auf diesen Seiten eine fundierte theoretische Weiterentwicklung an der Schnittstelle von Digitalisierung und Gerechtigkeit sowie neue methodische Hinweise. Praktiker sollen von dem Handlungsrahmen „Designing for Digital Justice Model“ profitieren, der drei Handlungsfelder für die Gestaltung besserer Justizsysteme bietet. Nur wenn wir die digitalen, rechtlichen und sozialen Akteure berücksichtigen, können wir bessere Systeme entwerfen, die sich für den Zugang zur Justiz, die Rechtsstaatlichkeit und letztlich den sozialen Frieden einsetzen. N2 - A principios de 2020, con la COVID-19, los tribunales de justicia de todo el mundo tuvieron que ponerse en línea para continuar con el servicio. Las tecnologías digitales materializaron las prácticas de los tribunales de formas impensables poco antes de la pandemia, creando resonancias con la regulación judicial y legal, así como fricciones. Comprender mejor las dinámicas en juego en la digitalización de los tribunales es primordial para diseñar sistemas de justicia que sirvan mejor a sus usuarios, garanticen una resolución de conflictos justa y oportuna y fomenten el acceso a la justicia. Sobre la base de tres grandes temas en la literatura -justicia electrónica, digitalización y organizaciones, e investigación del diseño-, Designing for Digital Justice adopta un enfoque matizado para tener en cuenta los organismos humanos y más que humanos. Utilizando un enfoque cualitativo, he estudiado en profundidad la digitalización de los tribunales chilenos durante la pandemia, concretamente entre abril de 2020 y septiembre de 2022. Aprovechando una amplia fuente de datos primarios y secundarios, he rastreado la genealogía de las nuevas materializaciones de las prácticas de los tribunales estructuradas por las posibilidades que ofrecen las tecnologías digitales. En cinco (5) estudios de caso, muestro en detalle cómo los tribunales llegaron a 1) trabajar a distancia, 2) celebrar audiencias por videoconferencia, 3) relacionarse con los usuarios a través de las redes sociales (es decir, Facebook y Chat Messenger), 4) emitir un espectáculo con jueces que responden a las preguntas de los usuarios a través de Facebook Live, y 5) grabar, transmitir y subir las audiencias judiciales a YouTube para cumplir con el requisito de publicidad de las audiencias penales. La digitalización de los tribunales durante la pandemia se caracteriza por una normatividad suspendida, que posibilita la innovación, pero presenta riesgos. Si bien las tecnologías digitales permitieron al poder judicial prestar servicios de forma continua, también crearon el riesgo de desplazar la normativa judicial y legal tradicional. Contribuyendo a la teoría de la innovación liminar y digitalización, Designing for Digital Justice teoriza cuatro fases: 1) la fase de pre-digitalización que da lugar al desarrollo de la regulación, 2) el hotspot de digitalización que da lugar a la ampliación de la regulación, 3) la innovación liminal que vuelve a desarrollar la regulación (pasando a una nueva fase preliminar), y 4) la permanencia de prácticas temporales que desplaza la regulación. Contribuyendo a la investigación sobre el diseño, Designing for Digital Justice ofrece nuevas posibilidades de intervención para el diseño de la justicia, conectando las tensiones y los niveles para intervenir en ellos. Los colegas investigadores encontrarán en estas páginas un sólido avance teórico en la intersección de la digitalización y la justicia y novedosas referencias metodológicas. Los profesionales se beneficiarán del marco de gobernanza Designing for Digital Justice Model, que ofrece tres campos de posibilidades de actuación para diseñar mejores sistemas de justicia. Sólo teniendo en cuenta las agencias digitales, jurídicas y sociales podremos diseñar mejores sistemas que se comprometan con el acceso a la justicia, el Estado de Derecho y, en última instancia, la paz social. KW - digitalisation KW - courts of justice KW - COVID-19 KW - Chile KW - online courts KW - design KW - law KW - organization studies KW - innovation KW - COVID-19 KW - Chile KW - Gerichtsbarkeit KW - Design KW - Digitalisierung KW - Innovation KW - Recht KW - Online-Gerichte KW - Organisationsstudien KW - COVID-19 KW - Chile KW - tribunales de justicia KW - diseño KW - digitalización KW - innovación KW - Derecho KW - tribunales en línea KW - estudios de organización Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-604178 ER -