Extended RDF as a Semantic Foundation of Rule Markup Languages

TL;DR

This paper introduces Extended RDF, a semantic framework that incorporates negation and derivation rules into RDF graphs, enabling more expressive reasoning with both open-world and closed-world assumptions.

Contribution

It extends RDF with weak and strong negation, derivation rules, and a stable model semantics based on Partial Logic, allowing for richer reasoning capabilities.

Findings

Supports both closed-world and open-world reasoning

Incorporates negation-as-failure and explicit negative information

Defines ERDF stable model semantics extending RDF(S)

Abstract

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-as-failure 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.