A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative reasoning: modeling and simulation with incomplete knowledge
Automatica (Journal of IFAC)
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
Current topics in qualitative reasoning
AI Magazine
Using triples for implementation: the triple20 ontology-manipulation tool
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Semantic techniques for enabling knowledge reuse in conceptual modelling
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part II
Semantic feedback for the enrichment of conceptual models
Proceedings of the sixth international conference on Knowledge capture
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The desire to share and reuse knowledge has led to the establishment of the Web Ontology Language (OWL) knowledge representation language. The Naturnet-Redime project needs to share qualitative knowledge models of issues relevant to sustainable development and OWL seems the obvious choice for representing such models to allow search and other activities relevant to sharing knowledge models. However, although the design choices made in OWL are properly documented, their implications for Artificial Intelligence (AI) are part of ongoing research. This paper explores the expressiveness of OWL by formalising the vocabulary and models used in Qualitative Reasoning (QR), and the applicability of OWL reasoners to solve QR problems. A parser has been developed to export (and import) the QR representations to (and from) OWL representations. To create the OWL definitions of the QR vocabulary and models, existing OWL patterns were used as much as possible. However, some new patterns, and pattern modifications, had to be developed in order to represent the QR vocabulary and models using OWL.