INGRIDKG: A FAIR Knowledge Graph of Graffiti

Graffiti is an urban phenomenon that is increasingly attracting the interest of the sciences. To the best of our knowledge, no<br> suitable data corpora are available for systematic research until now. The Information System Graffiti in Germany project<br> (INGRID) closes this gap by dealing with graffiti image collections that have been made available to the project for public<br> use. Within INGRID, the graffiti images are collected, digitized and annotated. With this work, we aim to support the rapid<br> access to a comprehensive data source on INGRID targeted especially by researchers. In particular, we present INGRIDKG, an<br> RDF knowledge graph of annotated graffiti, abides by the Linked Data and FAIR principles. We weekly update INGRIDKG<br> by augmenting the new annotated graffiti to our knowledge graph. Our generation pipeline applies RDF data conversion,<br> link discovery and data fusion approaches to the original data. The current version of INGRIDKG contains 460,640,154 triples<br> and is linked to 3 other knowledge graphs by over 200,000 links. In our use case studies, we demonstrate the usefulness of<br> our knowledge graph for different applications. INGRIDKG is publicly available under the Creative Commons Attribution 4.0<br> International license.