Managing knowledge in the human genetic variation (HGV) testing context

Authors:
Yulong Gu;James Warren;Jan Stanek
Affiliations:
Department of Computer Science-Tamaki, University of Auckland, New Zealand;Department of Computer Science-Tamaki, University of Auckland, New Zealand;Advanced Computing Research Centre, University of South Australia, Australia
Venue:
CSCWD'06 Proceedings of the 10th international conference on Computer supported cooperative work in design III
Year:
2006

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Abstract

Although human genetic variation (HGV) testing for clinical and research purposes produces much valuable data for health care and disease control, the knowledge management (KM) capability in this context is seldom reported or studied. We apply organizational KM theories to identify significant issues in managing HGV knowledge. We also review the essential quality of relevant KM technologies, such as database, data analysis tools, search engine, groupware, data submission tools and Workflow Management System (WfMS). Based on process analysis of key research activities in HGV testing, we propose a knowledge management system (KMS) approach to facilitate HGV knowledge flow and support cooperative HGV research work. By extending and integrating KM tools, a system architecture is designed to assist the key research procedures in HGV testing, to improve research documentation quality, to increase knowledge capture and dissemination, and to support the research cooperation and knowledge sharing in the domain.