I 24
Ontology/color space/quality dimensions/domains/Gärdenfors: these terms are theoretical constructs that are used in the systematization and explanation of our judgments.
Dimensions: are cognitive constructs that should not be mapped to wavelengths or other physical objects. Whether these dimensions correspond to neuronal structures, I will not discuss.
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I 258
Ontologies/Databases/Knowledge Representation/Gärdenfors: Noy and McGuinnes (2001)
(1) Thesis: There are excellent reasons to develop ontologies:
To enable common understanding of information structures,
In order to reuse domain-related knowledge,
To make knowledge about domains explicit,
To distinguish knowledge about domains from procedural knowledge,
To analyze domain knowledge.
Gärdenfors: the question is whether the ontologies as we know them from the Semantic Web are the appropriate means to achieve these goals. The semantics of terms is about much more, as my approach shows.
Ontologies/Semantic Web: in fact, there are many different ontologies in different languages that partially overlap. Formalisms have to do with integration problems such as structural and semantic inhomogeneity, inconsistencies and redundancies. (Visser, 2004)
(2).
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Ontology/Semantic Web/Gärdenfors: when we consider how people deal with concepts, then the class structures mostly capture similarities between the objects. (Goldstone, 1994
(3), Gärdenfors, 2000
(4)).
Problem: precisely a term like similarity cannot be expressed in the ontology of the Semantic Web.
1. Noy, N. F. & McGuinnes, M. L. (2001). Ontology development 101: A guide to creating your first ontology. Stanford Knowledge Systems Laboratory Technical Report, Stanford, CA.
2. Visser, U. (. (2004) Inteligent information integration for the Semantic Web. Berlin: Springer.
3. Goldstone, R. L. (1994). The role of similarity in categorization: Providing a groundwork. Cognition, 52, 125-157.
4. Gärdenfors, P. (2000). Conceptual Spaces: The geometry of thought. Cambridge, MA: MIT Press.
