Research Summary: Datalog-Based Data Access Cristina Civili Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti Sapienza Universit` a di Roma, Italy civili @dis.uniroma1.it Abstract. This paper presents the research summary of a Ph.D. plan concerning the study of Ontology-Based Data Access (OBDA) for on- tologies expressed in Datalog-based formalisms, i.e., Datalog rules that allow the use of existential variables in the head. 1 Introduction The research project I am undertaking during my Ph.D. program carries on the work I started in my Master Thesis and concerns the use of Datalog-based formalisms as an alternative to Description Logics for modeling ontologies in Ontology-Based Data Access systems. The interest in ontological languages has both theoretical reasons and prac- tical implications in several fields such as Knowledge Representation, Semantic Web and Information Integration. Despite the existence in the literature of sev- eral works concerning this topic, the identification of an ontological language showing an acceptable balance between its expressive power and the computa- tional complexity of reasoning tasks is still an open challenge that is slowing down the commercial spread of semantic tools. I believe that Datalog-based formalisms could be the answer to this issue, therefore I am carrying forward a formal investigation on a broad family of languages, called Datalog ± . 2 Current State of the Art of the Research Field The last few years have seen a growing interest in ontologies, a flexible tool for the formalization of knowledge bases whose use in Semantic Web [4] and Information Integration is well-established. Lately, the focus has been on their application to data access: Ontology- Based Data Access (OBDA) systems are a new promising frontier for knowledge representation and database research. In OBDA systems, ontologies are used as an additional layer of information placed upon traditional databases with the purpose of semantically enriching them. Typically, the ontology contains only the terminological part of the knowl- edge base, while the DBMS is used to manage the actual data. Query answering in such systems is often accomplished through expansion techniques, such as query rewriting [6, 14, 8].