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A framework for modular ERDF ontologies
March 2013
AnalytiADP13_AMAI
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.
Journal
Anastasia Analyti, Grigoris Antoniou, Carlos Viegas Damásio, Ioannis Pachoulakis
Annals of Mathematics in Artificial Intelligence
Springer Netherlands
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67
3-4
189-249
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1012-2443
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http://link.springer.com/article/10.1007%2Fs10472-013-9350-1
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Anastasia Analyti and Grigoris Antoniou and Carlos Viegas Damásio and Ioannis Pachoulakis, A framework for modular ERDF ontologies, Annals of Mathematics in Artificial Intelligence, Vol. 67, No. 3-4, Pag. 189-249, Springer Netherlands, ISSN 1012-2443, (http://link.springer.com/article/10.1007%2Fs10472-013-9350-1), March 2013.
<b>Anastasia Analyti, Grigoris Antoniou, <a href="/people/members/view.php?code=feecf7159d8e22c70a3bf33436444903" class="author">Carlos Viegas Damásio</a> and Ioannis Pachoulakis</b>, <u>A framework for modular ERDF ontologies</u>, Annals of Mathematics in Artificial Intelligence, Vol. 67, No. 3-4, Pag. 189-249, Springer Netherlands, ISSN 1012-2443, (<a href="http://link.springer.com/article/10.1007%2Fs10472-013-9350-1" target="_blank">url</a>), March 2013.
@article {AnalytiADP13_AMAI, author = {Anastasia Analyti and Grigoris Antoniou and Carlos Viegas Dam{\'a}sio and Ioannis Pachoulakis}, title = {A framework for modular ERDF ontologies}, journal = {Annals of Mathematics in Artificial Intelligence}, publisher = {Springer Netherlands}, volume = {67}, number = {3-4}, pages = {189-249}, issn = {1012-2443}, url = {http://link.springer.com/article/10.1007%2Fs10472-013-9350-1}, 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.}, month = {March}, year = {2013}, }
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