Modeling Distributed Knowledge Processes in Next Generation Multidisciplinary Alliances*

Information Systems Frontiers - 2000
Alaina G. Kanfer1, Caroline Haythornthwaite2, Bertram C. Bruce2, Geoffrey C. Bowker3, Nicholas C. Burbules2, Joseph F. Porac4, James Wade5
1National Center for Supercomputing Applications (NCSA), BORN, USA
2University of Illinois at Urbana-Champaign (UIUC), USA
3University of California, San Diego
4Emory University, USA
5University of Wisconsin, Madison

Tóm tắt

Current research on distributed knowledge processes suggests a critical conflict between knowledge processes in groups and the technologies built to support them. The conflict centers on observations that authentic and efficient knowledge creation and sharing is deeply embedded in an interpersonal face to face context, but that technologies to support distributed knowledge processes rely on the assumption that knowledge can be made mobile outside these specific contexts. This conflict is of growing national importance as work patterns change from same site to separate site collaboration, and millions of government and industrial dollars are invested in establishing academic-industry alliances and building infrastructures to support distributed collaboration and knowledge. In this paper we describe our multi-method approach for studying the tension between embedded and mobile knowledge in a project funded by the National Science Foundation's program on Knowledge and Distributed Intelligence. This project examines knowledge processes and technology in distributed, multidisciplinary scientific teams in the National Computational Science Alliance (Alliance), a prototypical next generation enterprise. First we review evidence for the tension between embedded and mobile knowledge in several research literatures. Then we present our three-factor conceptualization that considers how the interrelationships among characteristics of the knowledge shared, group context, and communications technology contribute to the tension between embedded and mobile knowledge. Based on this conceptualization we suggest that this dichotomy does not fully explain distributed multidisciplinary knowledge processes. Therefore we propose some alternate models of how knowledge is shared. We briefly introduce the setting in which we are studying distributed knowledge processes and finally, we describe the data collection methods and the current status of the project.

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