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Although RDF graphs have schema information associated with them, in practiceit is very common to find cases in which data do not fully conform to theirschema. A prominent example of this is DBpedia, which is RDF data extractedfrom Wikipedia, a publicly editable source of information. In such situations,it becomes interesting to study the structural properties of the actual data,because the schema gives an incomplete description of the organization of adataset. In this paper we have approached the study of the structuredness of anRDF graph in a principled way: we propose a framework for specifyingstructuredness functions, which gauge the degree to which an RDF graph conformsto a schema. In particular, we first define a formal language for specifyingstructuredness functions with expressions we call rules. This language allows auser or a database administrator to state a rule to which an RDF graph mayfully or partially conform. Then we consider the issue of discovering arefinement of a sort (type) by partitioning the dataset into subsets whosestructuredness is over a specified threshold. In particular, we prove that thenatural decision problem associated to this refinement problem is NP-complete,and we provide a natural translation of this problem into Integer LinearProgramming (ILP). Finally, we test this ILP solution with two real worlddatasets, DBpedia Persons and WordNet Nouns, and 4 different and intuitiverules, which gauge the structuredness in different ways. The rules givemeaningful refinements of the datasets, showing that our language can be apowerful tool for understanding the structure of RDF data.

A Principled Approach to Bridging the Gap between Graph Data and their Schemas