Using a Common-Sense Realistic Ontology: Making Data Models Better Map the World

Using a Common-Sense Realistic Ontology: Making Data Models Better Map the World

Ed Kazmierczak (The University of Melbourne, Australia) and Simon Milton (The University of Melbourne, Australia)
Copyright: © 2005 |Pages: 31
DOI: 10.4018/978-1-59140-339-5.ch008
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Abstract

This chapter examines the following question: “How well do data models map the world?” Data modelling languages are used in today’s information systems engineering environments to model reality. Many have a degree of hype surrounding their quality and applicability with narrow and specific justification often given in support of one over another. We want to more deeply understand the fundamental nature of data modelling languages. We thus propose a theory, based on ontology, that should allow us to understand, compare, evaluate, and strengthen data modelling languages. We then introduce Chisholm’s ontology and apply methods to analyse some data modelling languages using it. We find a good degree of overlap between all of the data modelling languages analysed and the core concepts of Chisholm’s ontology, and conclude that the data modelling languages investigated reflect an ontology of commonsense-realism. Critical common-sense realism more generally due to its perspectival nature and its implicit recognition of institutional and social reality has the potential to dramatically improve our ability to better map the world.

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