Which Knowledge Graph Is Best for Me?
This work addresses the challenge for researchers and developers in choosing the most suitable knowledge graph, though it is incremental as it builds on a prior survey.
The paper tackles the problem of comparing large, cross-domain knowledge graphs like DBpedia and Wikidata by applying data quality criteria and proposing a framework to help users select the best one for their needs, with simplified rules presented to ease access to their survey.
In recent years, DBpedia, Freebase, OpenCyc, Wikidata, and YAGO have been published as noteworthy large, cross-domain, and freely available knowledge graphs. Although extensively in use, these knowledge graphs are hard to compare against each other in a given setting. Thus, it is a challenge for researchers and developers to pick the best knowledge graph for their individual needs. In our recent survey, we devised and applied data quality criteria to the above-mentioned knowledge graphs. Furthermore, we proposed a framework for finding the most suitable knowledge graph for a given setting. With this paper we intend to ease the access to our in-depth survey by presenting simplified rules that map individual data quality requirements to specific knowledge graphs. However, this paper does not intend to replace our previously introduced decision-support framework. For an informed decision on which KG is best for you we still refer to our in-depth survey.