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Informatik 5
Information Systems
Prof. Dr. M. Jarke
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Dr. István Koren - Theses

Model-Based View Extraction With GraphQL - Open
Supervised by Prof. Dr. Matthias Jarke, Prof. Dr. Bernhard Rumpe; Advisor(s): Dr. István Koren, Manuela Dalibor
An Extensible Web Interface for Linked Data Platform Servers - Running
The Linked Data Platform (LDP) is a simple, standardized REST API that allows for the hierarchical organization of Linked Data, similar to a classical file system. While the standard is rather simple, manual interaction with the file system is tiresome and error prone. To simplify the interaction with the LDP server, a suitable web-based user interface for browsing, editing and visualizing LDP data with suitable Web Components should be developed in this work.
Building an Universal Community Success Awareness Gamifier - Running
Supervised by PD Dr. Ralf Klamma, AOR; Advisor(s): Dr. István Koren
Every community application can be gamitfied.
Retrofitting Industrial Machines on the Edge With WebAssembly - Running
Supervised by PD Dr. Ralf Klamma, AOR, Thomas Gries; Advisor(s): Dr. István Koren, Florian Brillowski
ENGLISH BELOW ↓ Datenstromverarbeitung an Industriemaschinen mit nativen Webtechnologien – Enabling sandboxed processing close to industrial machines with native web technologies.
Personalizing the User Interface of Requirements Bazaar - Finished
Completed by Milan Deruelle in 2020; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. H. Lichter; Advisor(s): Dr. István Koren
From End User Needs to New Products Using the House of Quality - Finished
Completed by Rafail Stankov in 2020; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. H. Lichter; Advisor(s): Dr. István Koren
Machine Vision im Umfeld der Mensch-Roboter-Kollaboration auf Basis der Microsoft Kinect - Finished
Completed by Justin Krause in 2018; Supervised by PD Dr. Ralf Klamma, AOR, Thomas Gries; Advisor(s): Marius Wiche, Florian Brillowski, Dr. István Koren
Das Ziel der Bachelorarbeit ist es, die Erkennung von Menschen im Nahfeld Roboter in einem industriellen Umfeld zu realisieren. Hierbei wird eine kostengünstige und weit verbreitete 3D-Kamera mit einer offenen Schnittstelle verwendet, die Microsoft Kinect V2. Sie stellt die nötigen Tiefeninformationen in Form einer Punktwolke zur Verfügung. Ein KUKA Greifarmroboter am ITA-Preformcenter wird dabei während der Entwicklung verwendet. Die Kommunikation zwischen der Kinect und der Bilderfassung soll dabei über MQTT, einem zeitgemäßen IoT Protokoll in industriellen Umgebungen, erfolgen. Durch eine umfassende Evaluation wird ausgewertet, wie zuverlässig die Erkennung funktioniert.
Infrastructuring for Crowdsourced Co-Design - Finished
Completed by Delcy Carolina Bonilla Oliva in 2018; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s): Dr. István Koren
Augmented Reality Human Performance and Workplace Modelling using Sensor Fusion Data - Finished
Completed by Rizwan Ali in 2018; Supervised by PD Dr. Ralf Klamma, AOR, Roland Klemke; Advisor(s): Dr. István Koren
An immersive Augmented Reality (AR training development framework needs support for combinations of a wide range of appropriate devices for different use cases. In a surgery training situation this can be an AR headset and a handtracking device capturing exact movements in order to evaluate the accuracy. Therefore, it is necessary to get information from different sensors and interpret them in a common sensor fusion framework, in order to record the actions. The goal of the thesis is twofold. First, the framework will be extended. New sensor hardware, which can be used to improve the training experience of apprentices, will be implemented, tested and evaluated against the given requirements. The implementation is based on the Unity SDK in combination with Microsoft HoloLens and other AR relevant devices. Second, we are interested in visual learning analytics of the gathered data. Therefore, means for storing learner traces both locally and externally will be evaluated with the intention to use the stored data for long-term analytics. Contributions will be specified and implemented with the help of the upcoming IEEE standard on Augmented Reality Learning Experience Models (ARLEM). As a Bachelor thesis, the scope can be adjusted.
A Gamification Framework for Mixed Reality Training - Finished
Completed by Benedikt Hensen in 2017; Supervised by PD Dr. Ralf Klamma, AOR, Dr. Andreas Herrler; Advisor(s): Dr. István Koren
In this thesis a framework will be developed which enables a gamified approach to training and learning in a mixed reality environment. The framework targets the Microsoft HoloLens and uses the Unity 3D Engine. It will support the 3D models of the Anatomy 2.0 web-application. Moreover, the framework can be customized by adding additional models in X3D-format. Furthermore, this work will explore the current gamification approaches and how they can be employed in mixed reality. Those methods and features will be elaborated in a medical use-case. It will provide a learning environment which can visualize and gamify the study of the human anatomy.
A Scalable Web-based Platform for Co-Design Activities - Finished
Completed by Huang, Yu-Wen in 2017; Supervised by PD Dr. Ralf Klamma, AOR, Prof. Dr. Matthias Jarke; Advisor(s): Dr. István Koren
Person Publications

Stefan Braun, István Koren, Marc Van Dyck, Matthias Jarke

An Agricultural Data Platform iStar Model

Proceedings of the Thirteenth International iStar Workshop co-located with 28th IEEE International Requirements Engineering Conference (RE 2020)

Lars Gleim, Tim Holzheim, István Koren, Stefan Decker

Automatic Bootstrapping of GraphQL Endpoints for RDF Triple Stores

Proceedings of the 4th Workshop on Storing, Querying, and Benchmarking the Web of Data (QuWeDa 2020) at ISWC'20, November 2-3 2020

Ralf Klamma, Daniel Sous, Benedikt Hensen, István Koren

Educational Escape Games for Mixed Reality

EC-TEL 2020. Addressing Global Challenges and Quality Education

More publications…