Improving RDF data with data mining Linked Open Data (LOD) comprises very many and often large public data sets and knowledge bases. Those datasets are mostly presented in the RDF triple structure of subject predicate and object where each triple represents a statement or fact. Unfortunately the heterogeneity of available open data requires significant integration steps before it can be used in applications. Meta information such as ontological definitions and exact range definitions of predicates are desirable and ideally provided by an ontology. However in the context of LOD ontologies are often incomplete or simply not available. Thus it is useful to automatically generate meta information such as ontological dependencies range definitions and topical classifications. Association rule mining which was originally applied for sales analysis on transactional databases is a promising and novel technique to explore such data. We designed an adaptation of this technique for min ing Rdf data and introduce the concept of “mining configurations” which allows us …