Generating SPARQL Executable Mappings to Integrate Ontologies

Data translation is an integration task that aims at populat- ing a target model with data of a source model by means of mappings. Generating them automatically is appealing insofar it may reduce inte- gration costs. Matching techniques automatically generate uninterpreted mappings, a.k.a. correspondences, that must be interpreted to perform the data translation task. Other techniques automatically generate ex- ecutable mappings, which encode an interpretation of these correspon- dences in a given query language. Unfortunately, current techniques to automatically generate executable mappings are based on instance ex- amples of the target model, which usually contains no data, or based on nested relational models, which cannot be straightforwardly applied to semantic-web ontologies. In this paper, we present a technique to auto- matically generate SPARQL executable mappings between OWL ontolo- gies. The original contributions of our technique are as follows: 1) it is not based on instance examples but on restrictions and correspondences, 2) we have devised an algorithm to make restrictions and correspondences explicit over a number of language-independent executable mappings, and 3) we have devised an algorithm to transform language-independent into SPARQL executable mappings. Finally, we evaluate our technique over ten scenarios and check that the interpretation of correspondences that it assumes is coherent with the expected results.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-