CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Evaluating ontological decisions with OntoClean
Communications of the ACM - Ontology: different ways of representing the same concept
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Supporting ontological analysis of taxonomic relationships
Data & Knowledge Engineering - ER2000
Sweetening Ontologies with DOLCE
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Spatial Dimensionality as a Classification Criterion for Qualities
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
Ontological analysis of taxonomic relationships
ER'00 Proceedings of the 19th international conference on Conceptual modeling
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What is needed to enable communication about observation and measurement results in information systems? Information system ontologies make a certain conceptualization explicit and partially account for the meanings of symbols associated with this conceptualization. Yet, the meaning of signs denoting measurement results such as “10 m”, “red” or “high” cannot be specified with currently available ontologies. They fail to separate the ontological nature of some observable quality from the specification of how to observe and name the measurement result. We employ the foundational ontology DOLCE for characterizing the ontological nature of observable magnitudes. This involves dealing with ontological questions like “What kinds of observable qualities exist, in which entity does the observed quality inhere and how are the magnitudes of the observed quality structured?”. Then, in order to capture the semantic aspects of an observation result, we introduce semantic reference spaces, which help deal with semantic questions like “Do the signs “10 m”, “33 feet” or “shallow” have the same meaning? Do these signs refer to the same entity, e.g. the depth magnitude of a lake? How to establish a unit of measure?". We posit that the semantic questions can be approached efficiently only if agreement is reached on the ontological questions, and show that the specification of the meaning of signs denoting measurement results is enabled via the extension of the foundational ontology DOLCE with semantic reference spaces.