TY - GEN A1 - Brand, Thomas A1 - Giese, Holger Burkhard T1 - Towards Generic Adaptive Monitoring T2 - 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO) N2 - Monitoring is a key prerequisite for self-adaptive software and many other forms of operating software. Monitoring relevant lower level phenomena like the occurrences of exceptions and diagnosis data requires to carefully examine which detailed information is really necessary and feasible to monitor. Adaptive monitoring permits observing a greater variety of details with less overhead, if most of the time the MAPE-K loop can operate using only a small subset of all those details. However, engineering such an adaptive monitoring is a major engineering effort on its own that further complicates the development of self-adaptive software. The proposed approach overcomes the outlined problems by providing generic adaptive monitoring via runtime models. It reduces the effort to introduce and apply adaptive monitoring by avoiding additional development effort for controlling the monitoring adaptation. Although the generic approach is independent from the monitoring purpose, it still allows for substantial savings regarding the monitoring resource consumption as demonstrated by an example. Y1 - 2019 SN - 978-1-5386-5172-8 U6 - https://doi.org/10.1109/SASO.2018.00027 SN - 1949-3673 SP - 156 EP - 161 PB - IEEE CY - New York ER - TY - GEN A1 - Blaesius, Thomas A1 - Eube, Jan A1 - Feldtkeller, Thomas A1 - Friedrich, Tobias A1 - Krejca, Martin Stefan A1 - Lagodzinski, Julius Albert Gregor A1 - Rothenberger, Ralf A1 - Severin, Julius A1 - Sommer, Fabian A1 - Trautmann, Justin T1 - Memory-restricted Routing With Tiled Map Data T2 - 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) N2 - Modern routing algorithms reduce query time by depending heavily on preprocessed data. The recently developed Navigation Data Standard (NDS) enforces a separation between algorithms and map data, rendering preprocessing inapplicable. Furthermore, map data is partitioned into tiles with respect to their geographic coordinates. With the limited memory found in portable devices, the number of tiles loaded becomes the major factor for run time. We study routing under these restrictions and present new algorithms as well as empirical evaluations. Our results show that, on average, the most efficient algorithm presented uses more than 20 times fewer tile loads than a normal A*. Y1 - 2018 SN - 978-1-5386-6650-0 U6 - https://doi.org/10.1109/SMC.2018.00567 SN - 1062-922X SP - 3347 EP - 3354 PB - IEEE CY - New York ER - TY - GEN A1 - Podlesny, Nikolai Jannik A1 - Kayem, Anne V. D. M. A1 - von Schorlemer, Stephan A1 - Uflacker, Matthias T1 - Minimising Information Loss on Anonymised High Dimensional Data with Greedy In-Memory Processing T2 - Database and Expert Systems Applications, DEXA 2018, PT I N2 - Minimising information loss on anonymised high dimensional data is important for data utility. Syntactic data anonymisation algorithms address this issue by generating datasets that are neither use-case specific nor dependent on runtime specifications. This results in anonymised datasets that can be re-used in different scenarios which is performance efficient. However, syntactic data anonymisation algorithms incur high information loss on high dimensional data, making the data unusable for analytics. In this paper, we propose an optimised exact quasi-identifier identification scheme, based on the notion of k-anonymity, to generate anonymised high dimensional datasets efficiently, and with low information loss. The optimised exact quasi-identifier identification scheme works by identifying and eliminating maximal partial unique column combination (mpUCC) attributes that endanger anonymity. By using in-memory processing to handle the attribute selection procedure, we significantly reduce the processing time required. We evaluated the effectiveness of our proposed approach with an enriched dataset drawn from multiple real-world data sources, and augmented with synthetic values generated in close alignment with the real-world data distributions. Our results indicate that in-memory processing drops attribute selection time for the mpUCC candidates from 400s to 100s, while significantly reducing information loss. In addition, we achieve a time complexity speed-up of O(3(n/3)) approximate to O(1.4422(n)). Y1 - 2018 SN - 978-3-319-98809-2 SN - 978-3-319-98808-5 U6 - https://doi.org/10.1007/978-3-319-98809-2_6 SN - 0302-9743 SN - 1611-3349 VL - 11029 SP - 85 EP - 100 PB - Springer CY - Cham 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 - GEN A1 - Gross, Sascha A1 - Tiwari, Abhishek A1 - Hammer, Christian T1 - PlAnalyzer BT - a precise approach for pendingIntent vulnerability analysis T2 - Computer Security(ESORICS 2018), PT II N2 - In this work we propose PIAnalyzer, a novel approach to analyze PendingIntent related vulnerabilities. We empirically evaluate PIAnalyzer on a set of 1000 randomly selected applications from the Google Play Store and find 1358 insecure usages of Pendinglntents, including 70 severe vulnerabilities. We manually inspected ten reported vulnerabilities out of which nine correctly reported vulnerabilities, indicating a high precision. The evaluation shows that PIAnalyzer is efficient with an average execution time of 13 seconds per application. KW - Android KW - Intent analysis KW - Information flow control KW - Static analysis Y1 - 2018 SN - 978-3-319-98989-1 SN - 978-3-319-98988-4 U6 - https://doi.org/10.1007/978-3-319-98989-1_3 SN - 0302-9743 SN - 1611-3349 VL - 11099 SP - 41 EP - 59 PB - Springer CY - Cham ER - TY - GEN A1 - Fricke, Andreas A1 - Döllner, Jürgen Roland Friedrich A1 - Asche, Hartmut T1 - Servicification - Trend or Paradigm Shift in Geospatial Data Processing? T2 - Computational Science and Its Applications – ICCSA 2018, PT III N2 - Currently we are witnessing profound changes in the geospatial domain. Driven by recent ICT developments, such as web services, serviceoriented computing or open-source software, an explosion of geodata and geospatial applications or rapidly growing communities of non-specialist users, the crucial issue is the provision and integration of geospatial intelligence in these rapidly changing, heterogeneous developments. This paper introduces the concept of Servicification into geospatial data processing. Its core idea is the provision of expertise through a flexible number of web-based software service modules. Selection and linkage of these services to user profiles, application tasks, data resources, or additional software allow for the compilation of flexible, time-sensitive geospatial data handling processes. Encapsulated in a string of discrete services, the approach presented here aims to provide non-specialist users with geospatial expertise required for the effective, professional solution of a defined application problem. Providing users with geospatial intelligence in the form of web-based, modular services, is a completely different approach to geospatial data processing. This novel concept puts geospatial intelligence, made available through services encapsulating rule bases and algorithms, in the centre and at the disposal of the users, regardless of their expertise. KW - Servicification KW - Geospatial intelligence KW - Spatial data handling systems Y1 - 2018 SN - 978-3-319-95168-3 SN - 978-3-319-95167-6 U6 - https://doi.org/10.1007/978-3-319-95168-3_23 SN - 0302-9743 SN - 1611-3349 VL - 10962 SP - 339 EP - 350 PB - Springer CY - Cham ER - TY - GEN A1 - Haarmann, Stephan A1 - Batoulis, Kimon A1 - Nikaj, Adriatik A1 - Weske, Mathias T1 - DMN Decision Execution on the Ethereum Blockchain T2 - Advanced Information Systems Engineering, CAISE 2018 N2 - Recently blockchain technology has been introduced to execute interacting business processes in a secure and transparent way. While the foundations for process enactment on blockchain have been researched, the execution of decisions on blockchain has not been addressed yet. In this paper we argue that decisions are an essential aspect of interacting business processes, and, therefore, also need to be executed on blockchain. The immutable representation of decision logic can be used by the interacting processes, so that decision taking will be more secure, more transparent, and better auditable. The approach is based on a mapping of the DMN language S-FEEL to Solidity code to be run on the Ethereum blockchain. The work is evaluated by a proof-of-concept prototype and an empirical cost evaluation. KW - Blockchain KW - Interacting processes KW - DMN Y1 - 2018 SN - 978-3-319-91563-0 SN - 978-3-319-91562-3 U6 - https://doi.org/10.1007/978-3-319-91563-0_20 SN - 0302-9743 SN - 1611-3349 VL - 10816 SP - 327 EP - 341 PB - Springer CY - Cham ER - TY - GEN A1 - Limberger, Daniel A1 - Gropler, Anne A1 - Buschmann, Stefan A1 - Döllner, Jürgen Roland Friedrich A1 - Wasty, Benjamin T1 - OpenLL BT - an API for Dynamic 2D and 3D Labeling T2 - 22nd International Conference Information Visualisation (IV) N2 - Today's rendering APIs lack robust functionality and capabilities for dynamic, real-time text rendering and labeling, which represent key requirements for 3D application design in many fields. As a consequence, most rendering systems are barely or not at all equipped with respective capabilities. This paper drafts the unified text rendering and labeling API OpenLL intended to complement common rendering APIs, frameworks, and transmission formats. For it, various uses of static and dynamic placement of labels are showcased and a text interaction technique is presented. Furthermore, API design constraints with respect to state-of-the-art text rendering techniques are discussed. This contribution is intended to initiate a community-driven specification of a free and open label library. KW - visualization KW - labeling KW - real-time rendering Y1 - 2018 SN - 978-1-5386-7202-0 U6 - https://doi.org/10.1109/iV.2018.00039 SP - 175 EP - 181 PB - IEEE CY - New York ER - TY - GEN A1 - Sianipar, Johannes Harungguan A1 - Sukmana, Muhammad Ihsan Haikal A1 - Meinel, Christoph T1 - Moving sensitive data against live memory dumping, spectre and meltdown attacks T2 - 26th International Conference on Systems Engineering (ICSEng) N2 - The emergence of cloud computing allows users to easily host their Virtual Machines with no up-front investment and the guarantee of always available anytime anywhere. But with the Virtual Machine (VM) is hosted outside of user's premise, the user loses the physical control of the VM as it could be running on untrusted host machines in the cloud. Malicious host administrator could launch live memory dumping, Spectre, or Meltdown attacks in order to extract sensitive information from the VM's memory, e.g. passwords or cryptographic keys of applications running in the VM. In this paper, inspired by the moving target defense (MTD) scheme, we propose a novel approach to increase the security of application's sensitive data in the VM by continuously moving the sensitive data among several memory allocations (blocks) in Random Access Memory (RAM). A movement function is added into the application source code in order for the function to be running concurrently with the application's main function. Our approach could reduce the possibility of VM's sensitive data in the memory to be leaked into memory dump file by 2 5% and secure the sensitive data from Spectre and Meltdown attacks. Our approach's overhead depends on the number and the size of the sensitive data. KW - Virtual Machine KW - Memory Dumping KW - Security KW - Cloud Computing KW - Spectre KW - Meltdown Y1 - 2019 SN - 978-1-5386-7834-3 PB - IEEE CY - New York ER - TY - GEN A1 - Risch, Julian A1 - Krestel, Ralf T1 - My Approach = Your Apparatus? BT - Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections T2 - Libraries N2 - Comparative text mining extends from genre analysis and political bias detection to the revelation of cultural and geographic differences, through to the search for prior art across patents and scientific papers. These applications use cross-collection topic modeling for the exploration, clustering, and comparison of large sets of documents, such as digital libraries. However, topic modeling on documents from different collections is challenging because of domain-specific vocabulary. We present a cross-collection topic model combined with automatic domain term extraction and phrase segmentation. This model distinguishes collection-specific and collection-independent words based on information entropy and reveals commonalities and differences of multiple text collections. We evaluate our model on patents, scientific papers, newspaper articles, forum posts, and Wikipedia articles. In comparison to state-of-the-art cross-collection topic modeling, our model achieves up to 13% higher topic coherence, up to 4% lower perplexity, and up to 31% higher document classification accuracy. More importantly, our approach is the first topic model that ensures disjunct general and specific word distributions, resulting in clear-cut topic representations. KW - Topic modeling KW - Automatic domain term extraction KW - Entropy Y1 - 2018 SN - 978-1-4503-5178-2 U6 - https://doi.org/10.1145/3197026.3197038 SN - 2575-7865 SN - 2575-8152 SP - 283 EP - 292 PB - Association for Computing Machinery CY - New York 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 - GEN A1 - Tala, Mahdi A1 - Schrape, Oliver A1 - Krstić, Miloš A1 - Bertozzi, Davide T1 - Exploring the Performance-Energy Optimization Space of a Bridge Between 3D-Stacked Electronic and Optical Networks-on-Chip T2 - XXXIII Conference on Design of Circuits and Integrated Systems (DCIS) N2 - The relentless improvement of silicon photonics is making optical interconnects and networks appealing for use in miniaturized systems, where electrical interconnects cannot keep up with the growing levels of core integration due to bandwidth density and power efficiency limitations. At the same time, solutions such as 3D stacking or 2.5D integration open the door to a fully dedicated process optimization for the photonic die. However, an architecture-level integration challenge arises between the electronic network and the optical one in such tightly-integrated parallel systems. It consists of adapting signaling rates, matching the different levels of communication parallelism, handling cross-domain flow control, addressing re-synchronization concerns, and avoiding protocol-dependent deadlock. The associated energy and performance overhead may offset the inherent benefits of the emerging technology itself. This paper explores a hybrid CMOS-ECL bridge architecture between 3D-stacked technology-heterogeneous networks-on-chip (NoCs). The different ways of overcoming the serialization challenge (i.e., through an improvement of the signaling rate and/or through space-/wavelength division multiplexing options) give rise to a configuration space that the paper explores, in search for the most energy-efficient configuration for high-performance. Y1 - 2018 SN - 978-1-7281-0171-2 U6 - https://doi.org/10.1109/DCIS.2018.8681461 SN - 2471-6170 SN - 2640-5563 PB - IEEE CY - New York ER - TY - GEN A1 - Reimann, Max A1 - Klingbeil, Mandy A1 - Pasewaldt, Sebastian A1 - Semmo, Amir A1 - Trapp, Matthias A1 - Döllner, Jürgen Roland Friedrich ED - Sourin, A Sourina T1 - MaeSTrO: A Mobile App for Style Transfer Orchestration using Neural Networks T2 - International Conference on Cyberworlds (CW) N2 - Mobile expressive rendering gained increasing popularity among users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles. However, when it comes to creative expression, the technology still faces inherent limitations in providing low-level controls for localized image stylization. This work enhances state-of-the-art neural style transfer techniques by a generalized user interface with interactive tools to facilitate a creative and localized editing process. Thereby, we first propose a problem characterization representing trade-offs between visual quality, run-time performance, and user control. We then present MaeSTrO, a mobile app for orchestration of neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors. At this, first user tests indicate different levels of satisfaction for the implemented techniques and interaction design. KW - non-photorealistic rendering KW - style transfer Y1 - 2018 SN - 978-1-5386-7315-7 U6 - https://doi.org/10.1109/CW.2018.00016 SP - 9 EP - 16 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 - GEN A1 - Sukmana, Muhammad Ihsan Haikal A1 - Torkura, Kennedy A. A1 - Cheng, Feng A1 - Meinel, Christoph A1 - Graupner, Hendrik T1 - Unified logging system for monitoring multiple cloud storage providers in cloud storage broker T2 - 32ND International Conference on Information Networking (ICOIN) N2 - With the increasing demand for personal and enterprise data storage service, Cloud Storage Broker (CSB) provides cloud storage service using multiple Cloud Service Providers (CSPs) with guaranteed Quality of Service (QoS), such as data availability and security. However monitoring cloud storage usage in multiple CSPs has become a challenge for CSB due to lack of standardized logging format for cloud services that causes each CSP to implement its own format. In this paper we propose a unified logging system that can be used by CSB to monitor cloud storage usage across multiple CSPs. We gather cloud storage log files from three different CSPs and normalise these into our proposed log format that can be used for further analysis process. We show that our work enables a coherent view suitable for data navigation, monitoring, and analytics. KW - Unified logging system KW - Cloud Service Provider KW - cloud monitoring KW - data integration KW - security analytics Y1 - 2018 SN - 978-1-5386-2290-2 U6 - https://doi.org/10.1109/ICOIN.2018.8343081 SP - 44 EP - 49 PB - IEEE CY - New York 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 - 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 - Richly, Keven T1 - Leveraging spatio-temporal soccer data to define a graphical query language for game recordings T2 - IEEE International Conference on Big Data (Big Data) N2 - For professional soccer clubs, performance and video analysis are an integral part of the preparation and post-processing of games. Coaches, scouts, and video analysts extract information about strengths and weaknesses of their team as well as opponents by manually analyzing video recordings of past games. Since video recordings are an unstructured data source, it is a complex and time-intensive task to find specific game situations and identify similar patterns. In this paper, we present a novel approach to detect patterns and situations (e.g., playmaking and ball passing of midfielders) based on trajectory data. The application uses the metaphor of a tactic board to offer a graphical query language. With this interactive tactic board, the user can model a game situation or mark a specific situation in the video recording for which all matching occurrences in various games are immediately displayed, and the user can directly jump to the corresponding game scene. Through the additional visualization of key performance indicators (e.g.,the physical load of the players), the user can get a better overall assessment of situations. With the capabilities to find specific game situations and complex patterns in video recordings, the interactive tactic board serves as a useful tool to improve the video analysis process of professional sports teams. KW - Spatio-temporal data analysis KW - soccer analytics KW - graphical query language Y1 - 2019 SN - 978-1-5386-5035-6 U6 - https://doi.org/10.1109/BigData.2018.8622159 SN - 2639-1589 SP - 3456 EP - 3463 PB - IEEE CY - New York 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 - GEN A1 - Teusner, Ralf A1 - Matthies, Christoph A1 - Staubitz, Thomas T1 - What Stays in Mind? BT - Retention Rates in Programming MOOCs T2 - IEEE Frontiers in Education Conference (FIE) Y1 - 2018 SN - 978-1-5386-1174-6 U6 - https://doi.org/10.1109/FIE.2018.8658890 SN - 0190-5848 PB - IEEE CY - New York ER -