DBpedia is a community effort that has created the most important cross-domain datasets in RDF, a focal point of the Linked Open Data (LOD) cloud. In its core there is a set of declarative mappings extracting the data from Wikipedia infoboxes and tables into the RDF. However, while DBpedia focuses on publishing knowledge in a machine-readable way, little attention has been paid to the benefits of supporting machine updates. This greatly restricts the possibilities of automatic curation of the DBpedia data that could be semi-automatically propagated to Wikipedia, and also prevents maintainers from evaluating the impact of their edits on the consistency of knowledge. Excluding the DBpedia taxonomy from the editing cycle is a major drawback which we aim to address. This paper starts a discussion of DBpedia making a case for a benchmark for Ontology Based Data Management (OBDM). As we show, although based on fairly restricted mappings (which we cast as a variant of nested tgds here) and minimalistic TBox language, accommodating DBpedia updates is intricate from different perspectives, ranging from conceptual (what is an adequate semantics for DBpe-dia SPARQL updates?) to challenges related to the user interface design.

A. Ahmeti, J.D. Fernandez, A. Polleres, V. Savenkov, Towards Updating Wikipedia via DBpedia Mappings and SPARQL. In: R. Pichler, A. Soares da Silva (Eds.), Proceedings of the 10th Alberto Mendelzon International Workshop on Foundations of Data Management, Panama, May 8–10, 2016. CEUR Workshop Proceedings 1644 (2016)