@article{RichlyBrauerSchlosser2020,
  author    = {Richly, Keven and Brauer, Janos and Schlosser, Rainer},
  title     = {Predicting location probabilities of drivers to improved dispatch decisions of transportation network companies based on trajectory data},
  series = {Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - ICORES},
  journal   = {Proceedings of the 9th International Conference on Operations Research and Enterprise Systems - ICORES},
  publisher = {Springer},
  address   = {Berlin},
  pages     = {12},
  year      = {2020},
  abstract  = {The demand for peer-to-peer ridesharing services increased over the last years rapidly. To cost-efficiently dispatch orders and communicate accurate pick-up times is challenging as the current location of each available driver is not exactly known since observed locations can be outdated for several seconds. The developed trajectory visualization tool enables transportation network companies to analyze dispatch processes and determine the causes of unexpected delays. As dispatching algorithms are based on the accuracy of arrival time predictions, we account for factors like noise, sample rate, technical and economic limitations as well as the duration of the entire process as they have an impact on the accuracy of spatio-temporal data. To improve dispatching strategies, we propose a prediction approach that provides a probability distribution for a driver's future locations based on patterns observed in past trajectories. We demonstrate the capabilities of our prediction results to ( i) avoid critical delays, (ii) to estimate waiting times with higher confidence, and (iii) to enable risk considerations in dispatching strategies.},
  language  = {en}
}
@article{KristineJonsonCarlonYokoiMauriceGayedetal.2023,
  author    = {Kristine Jonson Carlon, May and Yokoi, Kensuke and Maurice Gayed, John and Suyama, Hiroshi and Cross, Jeffrey},
  title     = {Preparing for Society 5.0 with MOOC Capabilities Extension},
  series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  journal   = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  editor    = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Cross, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  doi       = {10.25932/publishup-62080},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-620809},
  pages     = {9 -- 20},
  year      = {2023},
  abstract  = {Academia-industry collaborations are beneficial when both sides bring strengths to the partnership and the collaboration outcome is of mutual benefit. These types of collaboration projects are seen as a low-risk learning opportunity for both parties. In this paper, government initiatives that can change the business landscape and academia-industry collaborations that can provide upskilling opportunities to fill emerging business needs are discussed. In light of Japan's push for next-level modernization, a Japanese software company took a positive stance towards building new capabilities outside what it had been offering its customers. Consequently, an academic research group is laying out infrastructure for learning analytics research. An existing learning analytics dashboard was modularized to allow the research group to focus on natural language processing experiments while the software company explores a development framework suitable for data visualization techniques and artificial intelligence development. The results of this endeavor demonstrate that companies working with academia can creatively explore collaborations outside typical university-supported avenues.},
  language  = {en}
}
@article{ThomasStaubitzMeinel2023,
  author    = {Thomas, Max and Staubitz, Thomas and Meinel, Christoph},
  title     = {Preparing MOOChub metadata for the future of online learning},
  series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  journal   = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  editor    = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Scott, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  doi       = {10.25932/publishup-62483},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624830},
  pages     = {329 -- 338},
  year      = {2023},
  abstract  = {With the growing number of online learning resources, it becomes increasingly difficult and overwhelming to keep track of the latest developments and to find orientation in the plethora of offers. AI-driven services to recommend standalone learning resources or even complete learning paths are discussed as a possible solution for this challenge. To function properly, such services require a well-defined set of metadata provided by the learning resource. During the last few years, the so-called MOOChub metadata format has been established as a de-facto standard by a group of MOOC providers in German-speaking countries. This format, which is based on schema.org, already delivers a quite comprehensive set of metadata. So far, this set has been sufficient to list, display, sort, filter, and search for courses on several MOOC and open educational resources (OER) aggregators. AI recommendation services and further automated integration, beyond a plain listing, have special requirements, however. To optimize the format for proper support of such systems, several extensions and modifications have to be applied. We herein report on a set of suggested changes to prepare the format for this task.},
  language  = {en}
}
@book{SchneiderMaximovaGiese2022,
  author    = {Schneider, Sven and Maximova, Maria and Giese, Holger},
  title     = {Probabilistic metric temporal graph logic},
  number    = {146},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-532-3},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-54586},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-545867},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {34},
  year      = {2022},
  abstract  = {Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. When the states of the system can be represented by graphs, the rule-based formalism of Probabilistic Timed Graph Transformation Systems (PTGTSs) can be used to suitably capture structure dynamics as well as probabilistic and timed behavior of the system. The model checking support for PTGTSs w.r.t. properties specified using Probabilistic Timed Computation Tree Logic (PTCTL) has been already presented. Moreover, for timed graph-based runtime monitoring, Metric Temporal Graph Logic (MTGL) has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time. In this paper, we (a) extend MTGL to the Probabilistic Metric Temporal Graph Logic (PMTGL) by allowing for the specification of probabilistic properties, (b) adapt our MTGL satisfaction checking approach to PTGTSs, and (c) combine the approaches for PTCTL model checking and MTGL satisfaction checking to obtain a Bounded Model Checking (BMC) approach for PMTGL. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a running example.},
  language  = {en}
}
@book{SchneiderMaximovaGiese2021,
  author    = {Schneider, Sven and Maximova, Maria and Giese, Holger},
  title     = {Probabilistic metric temporal graph logic},
  number    = {140},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-517-0},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-51506},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-515066},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {40},
  year      = {2021},
  abstract  = {Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. When the states of the system can be represented by graphs, the rule-based formalism of Probabilistic Timed Graph Transformation Systems (PTGTSs) can be used to suitably capture structure dynamics as well as probabilistic and timed behavior of the system. The model checking support for PTGTSs w.r.t. properties specified using Probabilistic Timed Computation Tree Logic (PTCTL) has been already presented. Moreover, for timed graph-based runtime monitoring, Metric Temporal Graph Logic (MTGL) has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time. In this paper, we (a) extend MTGL to the Probabilistic Metric Temporal Graph Logic (PMTGL) by allowing for the specification of probabilistic properties, (b) adapt our MTGL satisfaction checking approach to PTGTSs, and (c) combine the approaches for PTCTL model checking and MTGL satisfaction checking to obtain a Bounded Model Checking (BMC) approach for PMTGL. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a running example.},
  language  = {en}
}
@article{ChristopherAshwoodBittremieuxDeutschetal.2020,
  author    = {Christopher Ashwood, Wout Bittremieux and Bittremieux, Wout and Deutsch, Eric W. and Doncheva, Nadezhda T. and Dorfer, Viktoria and Gabriels, Ralf and Gorshkov, Vladimir and Gupta, Surya and Jones, Andrew R. and K{\"a}ll, Lukas and Kopczynski, Dominik and Lane, Lydie and Lautenbacher, Ludwig and Legeay, Marc and Locard-Paulet, Marie and Mesuere, Bart and Sachsenberg, Timo and Salz, Renee and Samaras, Patroklos and Schiebenhoefer, Henning and Schmidt, Tobias and Schw{\"a}mmle, Veit and Soggiu, Alessio and Uszkoreit, Julian and Van Den Bossche, Tim and Van Puyvelde, Bart and Van Strien, Joeri and Verschaffelt, Pieter and Webel, Henry and Willems, Sander and Perez-Riverolab, Yasset and Netz, Eugen and Pfeuffer, Julianus},
  title     = {Proceedings of the EuBIC-MS 2020 Developers' Meeting},
  series = {EuPA Open Proteomics},
  volume    = {24},
  journal   = {EuPA Open Proteomics},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2212-9685},
  doi       = {10.1016/j.euprot.2020.11.001},
  pages     = {1 -- 6},
  year      = {2020},
  abstract  = {The 2020 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers' meeting was held from January 13th to January 17th 2020 in Nyborg, Denmark. Among the participants were scientists as well as developers working in the field of computational mass spectrometry (MS) and proteomics. The 4-day program was split between introductory keynote lectures and parallel hackathon sessions. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts, and to actively contribute to highly relevant research projects. We successfully produced several new tools that will be useful to the proteomics community by improving data analysis as well as facilitating future research. All keynote recordings are available on https://doi.org/10.5281/zenodo.3890181.},
  language  = {en}
}
@book{MeinelDoellnerWeskeetal.2021,
  author    = {Meinel, Christoph and D{\"o}llner, J{\"u}rgen Roland Friedrich and Weske, Mathias and Polze, Andreas and Hirschfeld, Robert and Naumann, Felix and Giese, Holger and Baudisch, Patrick and Friedrich, Tobias and B{\"o}ttinger, Erwin and Lippert, Christoph and D{\"o}rr, Christian and Lehmann, Anja and Renard, Bernhard and Rabl, Tilmann and Uebernickel, Falk and Arnrich, Bert and H{\"o}lzle, Katharina},
  title     = {Proceedings of the HPI Research School on Service-oriented Systems Engineering 2020 Fall Retreat},
  number    = {138},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-513-2},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-50413},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-504132},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {vi, 144},
  year      = {2021},
  abstract  = {Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application. Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.},
  language  = {en}
}
@article{XiaoxiaoShuangshuang2023,
  author    = {Xiaoxiao, Wang and Shuangshuang, Guo},
  title     = {Promoting global higher education cooperation},
  series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  journal   = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  editor    = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Scott, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  doi       = {10.25932/publishup-62386},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-623865},
  pages     = {85 -- 93},
  year      = {2023},
  abstract  = {The massive growth of MOOCs in 2011 laid the groundwork for the achievement of SDG 4. With the various benefits of MOOCs, there is also anticipation that online education should focus on more interactivity and global collaboration. In this context, the Global MOOC and Online Education Alliance (GMA) established a diverse group of 17 world-leading universities and three online education platforms from across 14 countries on all six continents in 2020. Through nearly three years of exploration, GMA has gained experience and achieved progress in fostering global cooperation in higher education. First, in joint teaching, GMA has promoted in-depth cooperation between members inside and outside the alliance. Examples include promoting the exchange of high-quality MOOCs, encouraging the creation of Global Hybrid Classroom, and launching Global Hybrid Classroom Certificate Programs. Second, in capacity building and knowledge sharing, GMA has launched Online Education Dialogues and the Global MOOC and Online Education Conference, inviting global experts to share best practices and attracting more than 10 million viewers around the world. Moreover, GMA is collaborating with international organizations to support teachers' professional growth, create an online learning community, and serve as a resource for further development. Third, in public advocacy, GMA has launched the SDG Hackathon and Global Massive Open Online Challenge (GMOOC) and attracted global learners to acquire knowledge and incubate their innovative ideas within a cross-cultural community to solve real-world problems that all humans face and jointly create a better future. Based on past experiences and challenges, GMA will explore more diverse cooperation models with more partners utilizing advanced technology, provide more support for digital transformation in higher education, and further promote global cooperation towards building a human community with a shared future.},
  language  = {en}
}
@book{SchwarzerWeissSaoumiKitteletal.2023,
  author    = {Schwarzer, Ingo and Weiß-Saoumi, Said and Kittel, Roland and Friedrich, Tobias and Kaynak, Koraltan and Durak, Cemil and Isbarn, Andreas and Diestel, J{\"o}rg and Knittel, Jens and Franz, Marquart and Morra, Carlos and Stahnke, Susanne and Braband, Jens and Dittmann, Johannes and Griebel, Stephan and Krampf, Andreas and Link, Martin and M{\"u}ller, Matthias and Radestock, Jens and Strub, Leo and Bleeke, Kai and Jehl, Leander and Kapitza, R{\"u}diger and Messadi, Ines and Schmidt, Stefan and Schwarz-R{\"u}sch, Signe and Pirl, Lukas and Schmid, Robert and Friedenberger, Dirk and Beilharz, Jossekin Jakob and Boockmeyer, Arne and Polze, Andreas and R{\"o}hrig, Ralf and Sch{\"a}be, Hendrik and Thiermann, Ricky},
  title     = {RailChain},
  number    = {152},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-550-7},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-57740},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-577409},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {140},
  year      = {2023},
  abstract  = {The RailChain project designed, implemented, and experimentally evaluated a juridical recorder that is based on a distributed consensus protocol. That juridical blockchain recorder has been realized as distributed ledger on board the advanced TrainLab (ICE-TD 605 017) of Deutsche Bahn. For the project, a consortium consisting of DB Systel, Siemens, Siemens Mobility, the Hasso Plattner Institute for Digital Engineering, Technische Universit{\"a}t Braunschweig, T{\"U}V Rheinland InterTraffic, and Spherity has been formed. These partners not only concentrated competencies in railway operation, computer science, regulation, and approval, but also combined experiences from industry, research from academia, and enthusiasm from startups. Distributed ledger technologies (DLTs) define distributed databases and express a digital protocol for transactions between business partners without the need for a trusted intermediary. The implementation of a blockchain with real-time requirements for the local network of a railway system (e.g., interlocking or train) allows to log data in the distributed system verifiably in real-time. For this, railway-specific assumptions can be leveraged to make modifications to standard blockchains protocols. EULYNX and OCORA (Open CCS On-board Reference Architecture) are parts of a future European reference architecture for control command and signalling (CCS, Reference CCS Architecture - RCA). Both architectural concepts outline heterogeneous IT systems with components from multiple manufacturers. Such systems introduce novel challenges for the approved and safety-relevant CCS of railways which were considered neither for road-side nor for on-board systems so far. Logging implementations, such as the common juridical recorder on vehicles, can no longer be realized as a central component of a single manufacturer. All centralized approaches are in question. The research project RailChain is funded by the mFUND program and gives practical evidence that distributed consensus protocols are a proper means to immutably (for legal purposes) store state information of many system components from multiple manufacturers. The results of RailChain have been published, prototypically implemented, and experimentally evaluated in large-scale field tests on the advanced TrainLab. At the same time, the project showed how RailChain can be integrated into the road-side and on-board architecture given by OCORA and EULYNX. Logged data can now be analysed sooner and also their trustworthiness is being increased. This enables, e.g., auditable predictive maintenance, because it is ensured that data is authentic and unmodified at any point in time.},
  language  = {en}
}
@article{EbnerEdelsbrunnerHohlaSejkoraetal.2023,
  author    = {Ebner, Martin and Edelsbrunner, Sarah and Hohla-Sejkora, Katharina and Lipp, Silvia and Sch{\"o}n, Sandra},
  title     = {Role of MOOCs and Imoox for Austrian Universities},
  series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  journal   = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  editor    = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Scott, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  doi       = {10.25932/publishup-62213},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-622134},
  pages     = {77 -- 84},
  year      = {2023},
  abstract  = {This research paper provides an overview of the current state of MOOCs (massive open online courses) and universities in Austria, focusing on the national MOOC platform iMooX.at. The study begins by presenting the results of an analysis of the performance agreements of 22 Austrian public universities for the period 2022-2024, with a specific focus on the mention of MOOC activities and iMooX. The authors find that 12 of 22 (55 \%) Austrian public universities use at least one of these terms, indicating a growing interest in MOOCs and online learning. Additionally, the authors analyze internal documentation data to share insights into how many universities in Austria have produced and/or used a MOOC on the iMooX platform since its launch in 2014. These findings provide a valuable measure of the current usage and monitoring of MOOCs and iMooX among Austrian higher education institutions. Overall, this research contributes to a better understanding of the current state of MOOCs and their integration within Austrian higher education.},
  language  = {en}
}