Timo Stegemann (former member)

Timo Stegemann joined the Interactive Systems Research Group after receiving a diploma degree in Computer Science from the University Duisburg-Essen in 2011. His main research interest is the visualization of semantic data and the resulting new opportunities for exploration and interaction of these data.

Since he joined the group, Timo has been involved in several funded research projects. In OPDM, he was involved in implementing a product management system to enable the creation of semantic product ontologies by non-technical users. In KOLEGEA, he was investigating novel representations for medical guidelines. Currently, he is involved in the DESUMA project, which will create interactive tools to foster the creation of intelligent product advisors.

Timo was one of the main developers of RelFinder – a tool for visualization of relationships in semantic data. In 2017, the corresponding paper Interactive Relationship Discovery via the Semantic Web from 2010 won the ESWC Best Paper 7 Year Award as most influential paper that was presented at this conference.

His main reaserch project is SemwidgJS. SemwidgJS is a JavaScript based library for displaying Semantic Widgets that enriches websites with UI elements whose data is queried from SPARQL endpoints. SemwidgJS supports creation of simple UI elements such as labels and links, interactive elements for data input and selection that can manipulate other widgets, but also complex elements for displaying charts and maps are available.

Thesis

Contact

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Publications

Pattern-based analysis of SPARQL queries from the LSQ dataset

Investigating Learnability, User Performance, and Preferences of the Path Query Language SemwidgQL Compared to SPARQL

The Role of Semantic Data in Engineering Interactive Systems

SemwidgJS: A Semantic Widget Library for the Rapid Development of User Interfaces for Linked Open Data

Interactive Construction of Semantic Widgets for Visualizing Semantic Web Data

Interacting with semantic data by using X3S

Interactive Relationship Discovery via the Semantic Web

The RelFinder User Interface: Interactive Exploration of Relationships between Objects of Interest

RelFinder: Revealing Relationships in RDF Knowledge Bases

Semantisch unterstützte Informationsextraktion aus Dokumentenmengen

InteractiveExtractor: Durchgängige Unterstützung bei der Extraktion von anforderungsrelevanten Informationen

Entdecken und Explorieren von Zusammenhängen im Semantic Web