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An Information Model Based on Classification Theory

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  • Jeffrey Parsons

    (Faculty of Business Administration, Memorial University of Newfoundland, St. John's, Newfoundland, Canada A1B 3X5)

Abstract

This paper develops a formal information structuring model based on the premise that an information system represents knowledge about things in an organization. Since humans organize knowledge about things via categories or classes, the model is motivated by a theory of classification. The theory suggests several critical elements of classification based on the importance of classifying things to human survival. These elements are reflected by constructs in the model. Formal implications of the model for systems development are derived and strategies proposed for empirically evaluating these implications with respect to current modeling approaches. Necessary conditions are identified for a collection of classes to be considered a "good" model of some domain. The conditions permit different users to classify the same objects in different ways, depending on need. This suggests a new approach to data or object modeling which emphasizes instances and properties, rather than fixed categories of data or schemas. The model also offers insights into the role of classification in object-oriented analysis and, design methodologies. Finally, a program of research is outlined in which the model is being used to develop and experimentally evaluate an information modeling methodology, and as a source of implementation primitives for "instance-based" data modeling.

Suggested Citation

  • Jeffrey Parsons, 1996. "An Information Model Based on Classification Theory," Management Science, INFORMS, vol. 42(10), pages 1437-1453, October.
    • Handle: RePEc:inm:ormnsc:v:42:y:1996:i:10:p:1437-1453
    DOI: 10.1287/mnsc.42.10.1437
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    Cited by:

    1. Seno-Alday, Sandra, 2010. "International business thought: A 50-year footprint," Journal of International Management, Elsevier, vol. 16(1), pages 16-31, March.
    2. Andrew Burton-Jones & Peter N. Meso, 2006. "Conceptualizing Systems for Understanding: An Empirical Test of Decomposition Principles in Object-Oriented Analysis," Information Systems Research, INFORMS, vol. 17(1), pages 38-60, March.
    3. Yair Wand & Ron Weber, 2002. "Research Commentary: Information Systems and Conceptual Modeling—A Research Agenda," Information Systems Research, INFORMS, vol. 13(4), pages 363-376, December.
    4. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.
    5. Roman Lukyanenko & Jeffrey Parsons & Yolanda F. Wiersma, 2014. "The IQ of the Crowd: Understanding and Improving Information Quality in Structured User-Generated Content," Information Systems Research, INFORMS, vol. 25(4), pages 669-689, December.

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