Querying Linked Data catalogues for concept URIs to describe research data
The reuse of well-known terminology in the shape of entities with unique identifiers is a key aspect in Linked Data. Different approaches exist on how to organize and provide referenceable entity instances in certain knowledge domains based on ontologies. Sources for relevant concepts are either instance data sets (e.g. DBpedia), dataset collections (e.g. lod.openlinksw.com ) or ontology catalogues (e.g. LoV).
The intended research internship project focuses on the retrieval of identifiers for data entities that are relevant for the description of digital research data, such as the type of research data, the main study object, the research methodology, the involved institution, the publication license or further relevant information. After identifying relevant concepts and requirements, it should be investigated how identifiers for instances of particular concepts can be obtained from one or multiple existing data sources. This might involve sequential follow-up or federated queries. A reflective discussion of the results should complete the project.