A framework for modular ERDF ontologies

Anastasia Analyti, Grigoris Antoniou, Carlos Viegas Damásio, Ioannis Pachoulakis

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

Original languageEnglish
Pages (from-to)189-249
Number of pages61
JournalAnnals of Mathematics and Artificial Intelligence
Volume67
Issue number3-4
DOIs
Publication statusPublished - 1 Mar 2013

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