RADAR knowledge graph and SPARQL endpoint

A knowledge graph is a structured representation of information that illustrates relationships between entities in a specific area. These entities and relationships are often represented in RDF triples (Subject-Predicate-Object). The graph organizes data into nodes (representing entities) and edges (representing relationships).

By modeling relationships between entities in this way, knowledge graphs enable a deeper understanding of data. They thus support precise and effective searches, queries and analyses that are not easily achieved in classical databases and facilitate navigation through complex knowledge spaces. Knowledge graphs also enable the semantic structuring of information, improving interoperability between different data sources and systems. In an increasingly interconnected and datadriven world, knowledge graphs are becoming more and more important.

We have recently started to regularly create a RADAR knowledge graph based on the Schema.org vocabulary. The RDF triples of all or selected RADAR datasets are updated daily and are available in turtle format (.ttl) at the following URLs:

• all RADAR datasets:  https://www.radar-service.eu/knowledgegraph 
• all RADAR4KIT datasets: https://radar.kit.edu/knowledgegraph 
• all RADAR4Culture datasets: https://radar4culture.radar-service.eu/knowledgegraph 
• all RADAR4Chem datasets: https://radar4chem.radar-service.eu/knowledgegraph 

RADAR also supports a SPARQL endpoint, which can be used to query the knowledge graph in a standardized and machine accessible way: https://www.radar-service.eu/sparql

Note: 

• RADAR4Chem is funded by NFDI4Chem (DFG Project Number 441958208)
• RADAR4Culture is funded by NFDI4Culture (DFG Project Number 441958017)