KNOWLEDGE REUSE THROUGH CHANCE DISCOVERY FROM AN ENTERPRISE DESIGN-BUILD ENTERPRISE DATA STORE

Author:

FRUCHTER RENATE1,OHSAWA YUKIO2,MATSUMURA NAOHIRO3

Affiliation:

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

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

3. 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.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Computer Science Applications,Human-Computer Interaction

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