Research

What is the research in the professorship about?

FAIR and Open Data. As part of the EU Data Act and the Research Data Act, data will increasingly be published as Open Data in compliance with the FAIR principles. The goal is to make data from research and administration findable and usable for relevant stakeholders. However, this requires the evaluation of new technologies in various areas. Important aspects include the development and assessment of semantic metadata vocabularies for DCAT data catalogs, legal frameworks, and lifecycle management related to the published data.

Knowledge Graphs and Data Integration. Knowledge graphs and the associated integration of distributed data are increasingly playing a central role in the global information landscape of the web. Key aspects, such as the Semantic Web (utilizing the W3C standards RDF/RDFS/OWL) and Linked Data, remain the subject of intensive research. This research leverages technologies from the web that are familiar to most web developers, such as protocols like HTTP and identification concepts like IRIs, URIs, and URNs. Through this evolving network of information, data can be linked to conceptual descriptions and contextual information (semantics), enabling the exploration, utilization, enhancement, and revision of informational building blocks across organizational boundaries. This facilitates more efficient data integration processes, which will also reshape traditional migration tasks. A particularly significant aspect of creating knowledge graphs is the integration and adaptation of data from legacy systems. This involves heterogeneous, sometimes highly complex conversion mechanisms to integrate various languages (e.g., SPARQL2SQL, RDB2RDF).

Analysis and evaluation of data, support processes for data sciences. Another aspect of research in the field of data management is related to technologies from the field of artificial intelligence. Large Language Models (LLMs) are currently being investigated in order to understand their advantages and disadvantages as well as possible applications in various social areas, industrial environments and research disciplines. On the one hand, the extent to which the combination of knowledge graphs and LLMs improves the use of data (transparency, explainability, timeliness, …) is examined. On the other hand, the use of LLMs in concept and schema creation is being researched. The integration of APIs with LLMs (such as ChatGPT, BERT, LLAMA etc.) in combination with integrated development environments (IDEs) is particularly exciting. Other supporting activities come from the area of ontology evolution and repair. There is also great interest in the connection of APIs in data management tools, which enable efficient and qualitative pipelining of data and services.

Veröffentlichungen

For all current publications please visit the link HIER