Ricerc@Sapienza

The quantitative evaluation of research is currently carried out by means of indicators calculated on data extracted and integrated by analysts who elaborate them by creating illustrative tables and plots of results. In this paper we propose a new approach which is able to move forward, from indicators’ development to performance model’s development. It combines the advantages of the Ontology-based data Access (OBDA) integration with the flexibility and robustness of a Visual Analytics (VA) environment. A detailed description of such an approach is presented in the paper.

It is well-known that answering conjunctive queries with inequalities (CQ≠s) over DL-LiteR ontologies is in general undecidable. In this paper we consider the subclass of CQ≠s, called CQ≠,bs, where inequalities involve only distinguished variables or individuals. In particular, we tackle the problem of answering C≠,bs and unions thereof (UC≠,bs s) over DL-LiteR≠ ontologies, where DL-LiteR≠ corresponds to DL-LiteR without the Unique Name Assumption, and with the possibility of asserting inequalities between individuals, as in OWL 2 QL.