R-DEVICE: A Deductive RDF Rule Language

Ontologies are pervading many areas of knowledge representation and management. To date, most research efforts have been spent on the development of sufficiently expressive languages for the representation and querying of ontologies; however, querying efficiency has received attention only recently, especially for ontologies referring to large amounts of data. In fact, it is still uncertain how reasoning tasks will scale when applied on massive amounts of data. This work is a first step toward this setting: based on a previous result showing that the SPARQL query language can be mapped to a Datalog, we show how efficient querying of big ontologies can be accomplished with a database oriented extension of the well known system DLV, recently developed. We report our initial results and we discuss about benefits of possible alternative data structures for representing RDF graphs in our architecture.

The Semantic Web: Research and …, 2007

Formal Methods for …, 2005

2008

Ontologies and automated reasoning are the building blocks of the Semantic Web initiative. Derivation rules can be included in an ontology to define derived concepts, based on base concepts. For example, rules allow to define the extension of a class or property, based on a complex relation between the extensions of the same or other classes and properties. On the other hand, the inclusion of negative information both in the form of negation-asfailure and explicit negative information is also needed to enable various forms of reasoning. In this paper, we extend RDF graphs with weak and strong negation, as well as derivation rules. The ERDF stable model semantics of the extended framework (Extended RDF) is defined, extending RDF(S) semantics. A distinctive feature of our theory, which is based on Partial Logic, is that both truth and falsity extensions of properties and classes are considered, allowing for truth value gaps. Our framework supports both closed-world and open-world reasoning through the explicit representation of the particular closed-world assumptions and the ERDF ontological categories of total properties and total classes.

Principles and Practice of …, 2004

This paper presents DR-DEVICE, a system for defeasible reasoning on the Web. Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and inconsistent information. Such reasoning is, among others, useful for ontology integration, where conflicting information arises naturally; and for the modeling of business rules and policies, where rules with exceptions are often used. In this paper we describe these scenarios in more detail along with the implementation of the DR-DEVICE system, which is capable of reasoning about RDF data over multiple Web sources using defeasible logic rules. The system is implemented on top of CLIPS production rule system and builds upon R-DEVICE, an earlier deductive rule system over RDF data that also supports derived attribute and aggregate attribute rules. Rules can be expressed either in a native CLIPS-like language, or in an extension of the OO-RuleML syntax. The operational semantics of defeasible logic are implemented through compilation into the generic rule language of R-DEVICE. The paper includes a use case of a semantic web broker that reasons defeasibly about renting apartments based on buyer's requirements (expressed RuleML defeasible logic rules) and seller's advertisements (expressed in RDF).

Knowledge media in …, 2002

RDF(S) 1 constitutes a newly emerging standard for metadata that is about to turn the World Wide Web into a machine-understandable knowledge base. It is an XML application that allows for the denotation of facts and schemata in a web-compatible format, building on an elaborate objectmodel for describing concepts and relations. Thus, it might turn up as a natural choice for a widely-useable ontology description language. However, its lack of capabilities for describing the semantics of concepts and relations beyond those provided by inheritance mechanisms makes it a rather weak language for even the most austere knowledge-based system. This paper presents an approach for modeling ontologies in RDF(S) that also considers axioms as objects that are describable in RDF(S). Thus, we provide flexible, extensible, and adequate means for accessing and exchanging axioms in RDF(S). Our approach follows the spirit of the World Wide Web, as we do not assume a global axiom specification language that is too intractable for one purpose and too weak for the next, but rather a methodology that allows (communities of) users to specify what axioms are interesting in their domain.

2007

RDF is an emerging knowledge representation formalism proposed by the W3C. A central feature of RDF are blank nodes, which allow to assert the existence of an entity without naming for it. Despite the importance of blank nodes for RDF, many existing RDF query language have only insu cient support for blank nodes. We propose a query language for RDF, called RDFLog, with extensive blank node support. ¿e evaluation of RDFLog may be reduced to the evaluation of Datalog. ¿is allows to apply standard database technology to querying RDF. Our Experimental evaluation shows that our implementation scales well, even for large data sets. ¿e core feature of the reduction is Skolemisation and an new form of unSkolemisation. In contrast to previous de nitions of un-Skolemisation our un-Skolemisation has desirable symmetric properties to those of the Skolemisation. We de ne a hierarchy of syntactical restrictions of RDFLog with lower expressivity but better complexity, thereby showing the computati...

Lecture Notes in Computer Science, 2015

We present Rubya, a tool that automatically generates the RDF view defined on top of relational data and all rules required for the incremental maintenance of the RDF view. Our approach relies on the designer to specify a mapping between the relational schema and a target ontology and results in a specification of how to represent relational schema concepts in terms of RDF classes and properties of the designers choice. Based on this mapping, the rules for incrementally maintenance of the RDF view are generated.