Presented at: Joint Workshop on Knowledge Evolution and Ontology Dynamics (EvoDyn2011)
by Markus Luczak-Rösch, Markus Bischoff
The Linked Data initiative gained momentum inside as well as outside of theresearch community. Thus, it is already an accepted research issue to investigate usage mining in the context ofthe Web of Data from various perspectives. We are currently working onan approach that applies such usage mining methods and analysis to support ontology and datasetmaintenance tasks. This paper presents one part of this work, namely a methodto detect errors or weaknesses within ontologies used for Linked Data populationbased on statistics and network visualizations. We contribute a detailed description of a log file preprocessing algorithm for Web of Data endpoints, a set of statistical measures that help to visualize different usage aspects, and an examplary analysis of one of the most prominent Linked Data set -- DBpedia -- aimed to show the feasibility and the potential of our approach.
Resource URI on the dog food server: http://data.semanticweb.org/workshop/evodyn/2011/paper/1
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