Domenico Fabio Savo

The MASTRO system for ontology-based data access

In this paper we present MASTRO, a Java tool for ontology-based data access (OBDA) developed at Sapienza Universita di Roma and at the Free University of Bozen-Bolzano. MASTRO manages OBDA systems in which the ontology is specified in DL-Lite A,id, a logic of the DL-Lite family of tractable Description Logics specifically tailored to ontology-based data access, and is connected to external JDBC enabled data management systems through semantic mappings that associate SQL queries over the external data to the elements of the ontology. Advanced forms of integrity constraints, which turned out to be very useful in practical applications, are also enabled over the ontologies. Optimized algorithms for answering expressive queries are provided, as well as features for intensional reasoning and consistency checking. MASTRO provides a proprietary API, an OWLAPI compatible interface, and a plugin for the Protege 4 ontology editor. It has been successfully used in several projects carried out in collaboration with important organizations, on which we briefly comment in this paper.

Inconsistency-tolerant semantics for description logics

We address the problem of dealing with inconsistencies in Description Logic (DL) knowledge bases. Our general goal is both to study DL semantical frameworks which are inconsistency-tolerant, and to devise techniques for answering unions of conjunctive queries posed to DL knowledge bases under such inconsistency-tolerant semantics. Our work is inspired by the approaches to consistent query answering in databases, which are based on the idea of living with inconsistencies in the database, but trying to obtain only consistent information during query answering, by relying on the notion of database repair. We show that, if we use the notion of repair studied in databases, inconsistency-tolerant query answering is intractable, even for the simplest form of queries. Therefore, we study different variants of the repair-based semantics, with the goal of reaching a good compromise between expressive power of the semantics and computational complexity of inconsistency-tolerant query answering.

Optimizing query rewriting in ontology-based data access

In ontology-based data access (OBDA), an ontology is connected to autonomous, and generally pre-existing, data repositories through mappings, so as to provide a high-level, conceptual view over such data. User queries are posed over the ontology, and answers are computed by reasoning both on the ontology and the mappings. Query answering in OBDA systems is typically performed through a query rewriting approach which is divided into two steps: (i) the query is rewritten with respect to the ontology (ontology rewriting of the query); (ii) the query thus obtained is then reformulated over the database schema using the mapping assertions (mapping rewriting of the query). In this paper we present a new approach to the optimization of query rewriting in OBDA. The key ideas of our approach are the usage of inclusion between mapping views and the usage of perfect mappings, which allow us to drastically lower the combinatorial explosion due to mapping rewriting. These ideas are formalized in PerfectMap, an algorithm for OBDA query rewriting. We have experimented PerfectMap in a real-world OBDA scenario: our experimental results clearly show that, in such a scenario, the optimizations of PerfectMap are crucial to effectively perform query answering.

Mastro studio: managing ontology-based data access applications

Ontology-based data access (OBDA) is a novel paradigm for accessing large data repositories through an ontology, that is a formal description of a domain of interest. Supporting the management of OBDA applications poses new challenges, as it requires to provide effective tools for (i) allowing both expert and non-expert users to analyze the OBDA specification, (ii) collaboratively documenting the ontology, (iii) exploiting OBDA services, such as query answering and automated reasoning over ontologies, e.g., to support data quality check, and (iv) tuning the OBDA application towards optimized performances. To fulfill these challenges, we have built a novel system, called MASTRO STUDIO, based on a tool for automated reasoning over ontologies, enhanced with a suite of tools and optimization facilities for managing OBDA applications. To show the effectiveness of MASTRO STUDIO, we demonstrate its usage in one OBDA application developed in collaboration with the Italian Ministry of Economy and Finance.

Query rewriting for inconsistent DL-lite ontologies

In this paper we study the problem of obtaining meaningful answers to queries posed over inconsistent DL-Lite ontologies. We consider different variants of inconsistency-tolerant semantics and show that for some of such variants answering unions of conjunctive queries (UCQs) is first-order (FOL) rewritable, i.e., it can be reduced to standard evaluation of a FOL/SQL query over a database. Since FOL-rewritability of query answering for UCQs over consistent ontologies under first-order logic semantics is one of the distinguishing features of DL-Lite, in this paper we actually identify some settings in which such property is preserved also under inconsistency-tolerant semantics. We therefore show that in such settings inconsistency-tolerant query answering has the same computational complexity of standard query answering and that it can rely on well-established relational database technology, as under standard DL semantics.

Effective Computation of Maximal Sound Approximations of Description Logic Ontologies

We study the problem of approximating Description Logic (DL) ontologies specified in a source language

Graph-based ontology classification in OWL 2 QL

\mathcal{L}_S

Updating inconsistent Description Logic knowledge bases

in terms of a less expressive target language

Mapping Analysis in Ontology-Based Data Access: Algorithms and Complexity

\mathcal{L}_T

Mapping Repair in Ontology-based Data Access Evolving Systems

. This problem is getting very relevant in practice: e.g., approximation is often needed in ontology-based data access systems, which are able to deal with ontology languages of a limited expressiveness. We first provide a general, parametric, and semantically well-founded definition of maximal sound approximation of a DL ontology. Then, we present an algorithm that is able to effectively compute two different notions of maximal sound approximation according to the above parametric semantics when the source ontology language is OWL 2 and the target ontology language is OWL 2 QL. Finally, we experiment the above algorithm by computing the two OWL 2 QL approximations of a large set of existing OWL 2 ontologies. The experimental results allow us both to evaluate the effectiveness of the proposed notions of approximation and to compare the two different notions of approximation in real cases.