Intelligent Information Management

The Resource Description Framework (RDF) is a W3C standard for representing data as triples, forming a flexible graph. While the RDF data model facilitates data integration and interoperability, its graph-based structure makes visualization challenging. Existing visualization approaches typically rely on manually defined mappings from RDF structures to UI components. While this can be effective for specific use cases, this solution approach introduces a tight coupling to particular ontologies and requires continuous maintenance as the underlying data model evolves.

This master’s thesis project should investigate a shape-based approach to RDF visualization. The Shapes Expressions Language (ShEx) enables the formal description of constraints on nodes and structure. Building on this, a modular framework should be designed to analyze ShEx schemas, identify recurring structural patterns, and automatically map them to suitable UI components. To this end, the first step is to conduct a requirements analysis and to systematically review the state of the art in RDF data visualization. Existing visualization approaches need to be classified and evaluated against the identified requirements. Based on these findings, a prototype of the proposed framework needs to be conceptualized and implemented. Finally, the prototype needs to be evaluated in a suitable evaluation, including a usability evaluation.