Catálogo de publicaciones - libros

For the foreseeable future, most data will continue to be stored in relational databases. To work with these data in ontology-based applications, tools and techniques that bridge the two models are required. Mapping all relational data to ontology instances is often not practical so dynamic data access approaches are typically employed, though these approaches can still suffer from scalability problems. The use of rules with these systems presents an opportunity to employ optimization techniques that can significantly reduce the amount of data transferred from databases. To illustrate this premise, we have developed tools that allow direct access to relational data from OWL applications. We express these data requirements by using extensions to OWL’s rule language SWRL. A variety of optimization techniques ensure that this process is efficient and scales to large data sets.

We describe a procedural, query answering-oriented semantics for weighted fuzzy logic programs. The computation of the semantics combines resolution with tabling methodologies and is done by constructing and evaluating an appropriate resolution graph.

This work presents a visualization algorithm for defeasible logic rule bases as well as a software tool that applies this algorithm, according to which, a directed graph is produced that represents the rule base. The graph features distinct node types for rules and atomic formulas and distinct connection types for the various rule types of defeasible logic.

We report on efficiency evaluations concerning two different approaches to using logic programming for OWL [1] reasoning and show, how the two approaches can be combined.

Schema mappings play a central role in both data integration and data exchange, and are understood as high-level specifications describing the relationships between data schemas. Based on these specifications, data structured under a source schema can be transformed into data structured under a target schema. During the transformation some structural constraints, both contextfree (the structure) and contextual (e.g. keys and value dependencies) should be taken into account. In this work, we present a formalism for schema mapping specification taking into account key constraints and value dependencies. The formalism extends results from [1,2], and our previous work [3,4]. We illustrate the approach by an example.

We use situation theory to model context of agents’ actions in heterogeneous P2P system of semantic data integration. This formal basis is also suitable to cope with information partiality, open-world and non-monotonic reasoning. Operational semantics of asking and answering queries by the agents is presented as a set of context-dependent rules. Situations are represented by facts and rules and Prolog-like reasoning mechanisms are used in the system. Specification of sample actions is presented.