INGRIDKG: A FAIR Knowledge Graph of Graffiti

Area of Science:

• Urban studies
• Digital humanities
• Computer science

Background:

• Graffiti is an urban phenomenon of growing scientific interest.
• Existing data corpora for systematic graffiti research are lacking.
• The Information System Graffiti in Germany project (INGRID) addresses this gap.

Purpose of the Study:

• To provide researchers with rapid access to a comprehensive data source on graffiti.
• To establish a structured and queryable knowledge base for graffiti research.
• To promote the principles of Linked Data and FAIR data management.

Main Methods:

• Collection, digitization, and annotation of graffiti image collections.
• Development of INGRIDKG, an RDF knowledge graph.
• Implementation of a generation pipeline involving RDF data conversion, link discovery, and data fusion.
• Weekly updates to INGRIDKG with newly annotated graffiti.

Main Results:

• Creation of INGRIDKG, a large-scale RDF knowledge graph of annotated graffiti.
• INGRIDKG currently contains over 460 million triples.
• The knowledge graph is linked to 3 external knowledge graphs via more than 200,000 links.
• Use case studies demonstrate the utility of INGRIDKG for various research applications.

Conclusions:

• INGRIDKG provides a valuable, FAIR-compliant resource for systematic research on graffiti.
• The knowledge graph facilitates diverse applications and interdisciplinary studies.
• The project successfully bridges the gap in available data for graffiti research.