Discovery and diagnosis of wrong SPARQL queries with ontology and constraint reasoning

Abstract

The discovery and diagnosis of wrong queries in database query languages have gained more attention in recent years. While for imperative languages well-known and mature debugging tools exist, the case of database query languages has traditionally attracted less attention. SPARQL is a database query language proposed for the retrieval of information in Semantic Web resources. RDF and OWL are standardized formats for representing Semantic Web information, and SPARQL acts on RDF/OWL resources allowing to retrieve answers of user’s queries. In spite of the SPARQL apparent simplicity, the number of mistakes a user can make in queries can be high and their detection, localization, and correction can be difficult to carry out. Wrong queries have as consequence most of the times empty answers, but also wrong and missing (expected but not found) answers. In this paper we present two ontology and constraint reasoning based methods for the discovery and diagnosis of wrong queries in SPARQL. The first method is used for detecting wrongly typed and unsatisfiable queries. The second method is used for detecting mismatching between user intention and queries, reporting incomplete, faulty queries as well as counterexamples. We formally define the above concepts and a list of examples to illustrate the methods is shown. A Web online tool has been developed to analyze SPARQL queries according to the proposed methods.