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Collaborating Authors

Rosati

AAAI Conferences

We define generalized ontology-based production systems (GOPSs), which formalize a very general and powerful combination of ontologies and production systems. We show that GOPSs capture and generalize many existing formal notions of production systems. We introduce a powerful verification query language for GOPSs, which is able to express the most relevant formal properties of production systems previously considered in the literature. We establish a general sufficient condition for the decidability of answering verification queries over GOPSs.


Description Logic Knowledge and Action Bases

Journal of Artificial Intelligence Research

Description logic Knowledge and Action Bases (KAB) are a mechanism for providing both a semantically rich representation of the information on the domain of interest in terms of a description logic knowledge base and actions to change such information over time, possibly introducing new objects. We resort to a variant of DL-Lite where the unique name assumption is not enforced and where equality between objects may be asserted and inferred. Actions are specified as sets of conditional effects, where conditions are based on epistemic queries over the knowledge base (TBox and ABox), and effects are expressed in terms of new ABoxes. In this setting, we address verification of temporal properties expressed in a variant of first-order mu-calculus with quantification across states. Notably, we show decidability of verification, under a suitable restriction inspired by the notion of weak acyclicity in data exchange.


Instance-Level Update in DL-Lite Ontologies through First-Order Rewriting

Journal of Artificial Intelligence Research

In this paper we study instance-level update in DL-LiteA , a well-known description logic that influenced the OWL 2 QL standard. Instance-level update regards insertions and deletions in the ABox of an ontology. In particular we focus on formula-based approaches to instance-level update. We show that DL-LiteA , which is well-known for enjoying first-order rewritability of query answering, enjoys a first-order rewritability property also for instance-level update. That is, every update can be reformulated into a set of insertion and deletion instructions computable through a non-recursive Datalog program with negation. Such a program is readily translatable into a first-order query over the ABox considered as a database, and hence into SQL. By exploiting this result, we implement an update component for DL-LiteA-based systems and perform some experiments showing that the approach works in practice.


Data Integration: A Logic-Based Perspective

AI Magazine

Data integration is the problem of combining data residing at different autonomous, heterogeneous sources and providing the client with a unified, reconciled global view of the data. We discuss dataintegration systems, taking the abstract viewpoint that the global view is an ontology expressed in a class-based formalism. We resort to an expressive description logic, ALCQI, that fully captures classbased representation formalisms, and we show that query answering in data integration, as well as all other relevant reasoning tasks, is decidable. However, when we have to deal with large amounts of data, the high computational complexity in the size of the data makes the use of a fullfledged expressive description logic infeasible in practice. This leads us to consider DL-Lite, a specifically tailored restriction of ALCQI that ensures tractability of query answering in data integration while keeping enough expressive power to capture the most relevant features of class-based formalisms.


Data Integration

AI Magazine

Data integration is the problem of combining data residing at different autonomous, heterogeneous sources and providing the client with a unified, reconciled global view of the data. We discuss dataintegration systems, taking the abstract viewpoint that the global view is an ontology expressed in a class-based formalism. We resort to an expressive description logic, ALCQI, that fully captures classbased representation formalisms, and we show that query answering in data integration, as well as all other relevant reasoning tasks, is decidable. However, when we have to deal with large amounts of data, the high computational complexity in the size of the data makes the use of a fullfledged expressive description logic infeasible in practice. This leads us to consider DL-Lite, a specifically tailored restriction of ALCQI that ensures tractability of query answering in data integration while keeping enough expressive power to capture the most relevant features of class-based formalisms.