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A collaborative framework for knowledge acquisition and management for bioinformatics applications

Title:

A collaborative framework for knowledge acquisition and management for bioinformatics applications

Hodaei Esfahani, Keywan (2008) A collaborative framework for knowledge acquisition and management for bioinformatics applications. Masters thesis, Concordia University.

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Abstract

We study Software Engineering Organizations (SEOs) in the area of Bioinformatics in the context of Knowledge Intensive Firms. From this perspective, we characterize the challenges SEOs may face in this area and show that the situation can be much improved by following proper knowledge management practices. In response to these challenges and considering the various software development activities in this area, we propose a Collaborative Knowledge Management Framework (CKMF). The framework has four components: data model, knowledge management database, constraints, and management committee. Data model has three layers and is the central knowledge repository and acts as knowledge transfer media. Knowledge management database stores and manages information about concepts and relationships captured in the data model layers. It can also support version management. Constraints encode the semantic integrity of the application domain. Managing committee is an elected body or committee in charge of defining and enforcing constraints and version management. Deploying the proposed framework, we can better identify, preserve, and institutionalize the knowledge possessed by the software developers. This will reduce the impact of attrition on SEOs, will ease steep learning curves for the Software Engineers new to the field or organization, will provide a history of knowledge evolution in the organization that can be used for postmortem analysis, and will greatly facilitate the flow of knowledge among the experts within and across organizational boundaries. We develop a prototype knowledge management of the proposed framework, and demonstrate a mapping between major needs and the framework elements. We also compare our approach with existing Bioinformatics Software Engineering tools and facilities. Our attempt in this work has been to offer a means for knowledge management in SEOs that captures individual creativity and team work, and acknowledges the importance and values of collective achievements at the same time.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Hodaei Esfahani, Keywan
Pagination:ix, 131 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M. Comp. Sc.
Program:Computer Science and Software Engineering
Date:2008
Thesis Supervisor(s):Shiri, Nematollaah
ID Code:976117
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:20
Last Modified:18 Jan 2018 17:41
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