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Knowledge Reuse Through Chance Discovery From An Enterprise Design-Build Enterprise Data Store

Author

Listed:
  • RENATE FRUCHTER

    (Director of Project Based Learning Laboratory (PBL Lab), Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305-4020, USA)

  • YUKIO OHSAWA

    (School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan)

  • NAOHIRO MATSUMURA

    (Graduate School of Economics, Osaka University, 1-7 Machikaneyama, Toyonaka, Osaka 560-0043, Japan)

Abstract

This paper explores the possibilities of chance discovery in building design and construction knowledge towards knowledge reuse from past project experiences captured in a enterprise data store. The proposed approach leverages two innovative technologies, (1) ThinkTank™, a web-based asynchronous collaboration technology developed at the Project Based Learning Lab at Stanford University that provides many of the advantages of face-to-face team meetings combined with the utility of e-mail and the organization of content in a database; and (2) Techniques of chance discovery, composed of the Double Helix process of chance discovery, and KeyGraph, a method of visualizing the content of human communications, developed in the laboratory of Chance Discovery at the University of Tsukuba. An overview of the ThinkTank™ and KeyGraph is presented. The validation testbed is described and a concrete scenario of chance discovery of reusable knowledge from a past project is presented to illustrate the value of linking an enterprise data store such as ThinkTank™ and KeyGraph. The paper concludes with a discussion of the importance of the double helix concept, i.e. first helix represented by the KeyGraph computer processing of the ThinkTank™ data, and the second helix represented by human interpretation and exploration of the KeyGraph representation of ThinkTank™ data. We emphasize that without the second helix, i.e. the human interpretation, contextualization and exploration of the results, the KeyGraph would offer only a visual representation of the data, but would not provide valuable input for decision making or knowledge reuse.

Suggested Citation

  • Renate Fruchter & Yukio Ohsawa & Naohiro Matsumura, 2005. "Knowledge Reuse Through Chance Discovery From An Enterprise Design-Build Enterprise Data Store," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 1(03), pages 393-406.
  • Handle: RePEc:wsi:nmncxx:v:01:y:2005:i:03:n:s1793005705000263
    DOI: 10.1142/S1793005705000263
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