Higher-Order Types and Information Modeling

Higher-Order Types and Information Modeling

Terry Halpin (Northface University, USA)
Copyright: © 2005 |Pages: 20
DOI: 10.4018/978-1-59140-471-2.ch010
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Abstract

While some information modeling approaches (e.g., the Relational Model and Object-Role Modeling) are typically formalized using first-order logic, other approaches to information modeling include support for higher-order types. There appear to be three main reasons for requiring higher-order types: (1) to permit instances of categorization types to be types themselves (e.g., the Unified Modeling Language introduced power types for this purpose); (2) to directly support quantification over sets and general concepts; (3) to specify business rules that cross levels/meta levels (or ignore level distinctions) in the same model. As the move to higher-order logic may add considerable complexity to the task of formalizing and implementing a modeling approach, it is worth investigating whether the same practical modeling objectives can be met while staying within a first-order framework. This chapter examines some key issues involved, suggests techniques for retaining a first-order formalization, and makes some suggestions for adopting a higher-order semantics.

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