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A Systematic Relationship Analysis for Modeling Information Domains

A Systematic Relationship Analysis for Modeling Information Domains

Joonhee Yoo, Michael Bieber
Copyright: © 2001 |Pages: 17
ISBN13: 9781878289773|ISBN10: 1878289772|EISBN13: 9781930708853
DOI: 10.4018/978-1-878289-77-3.ch024
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MLA

Yoo, Joonhee, and Michael Bieber. "A Systematic Relationship Analysis for Modeling Information Domains." Information Modeling in the New Millennium, edited by Matti Rossi and Keng Siau, IGI Global, 2001, pp. 150-166. https://doi.org/10.4018/978-1-878289-77-3.ch024

APA

Yoo, J. & Bieber, M. (2001). A Systematic Relationship Analysis for Modeling Information Domains. In M. Rossi & K. Siau (Eds.), Information Modeling in the New Millennium (pp. 150-166). IGI Global. https://doi.org/10.4018/978-1-878289-77-3.ch024

Chicago

Yoo, Joonhee, and Michael Bieber. "A Systematic Relationship Analysis for Modeling Information Domains." In Information Modeling in the New Millennium, edited by Matti Rossi and Keng Siau, 150-166. Hershey, PA: IGI Global, 2001. https://doi.org/10.4018/978-1-878289-77-3.ch024

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Abstract

Many conceptual modeling and system design methodologies provide tools to help system designers to model the real world. No guidelines exist, however, for determining the relationships within conceptual domains or implementations. RNA (Relationship Navigation Analysis), based on a generic relationship taxonomy, provides a systematic way of identifying useful relationships in application domains. Developers can then implement each relationship as a link. Viewing an application domain from the relationship management point of view and modeling from a philosophy of maximum access provides a unique vantage point for application design. We present RNA and its generic relationship taxonomy, describing their use for system analysis.

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