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A collaborative framework for knowledge acquisition and management for bioinformatics applications.

机译:用于生物信息学应用程序的知识获取和管理的协作框架。

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摘要

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.
机译:我们在知识密集型企业的背景下研究生物信息学领域的软件工程组织(SEO)。从这个角度来看,我们描述了SEO在此领域可能面临的挑战,并表明通过遵循正确的知识管理做法,可以大大改善这种情况。为了应对这些挑战并考虑该领域中的各种软件开发活动,我们提出了一个协作式知识管理框架(CKMF)。该框架包含四个组件:数据模型,知识管理数据库,约束和管理委员会。数据模型具有三层,是中央知识存储库,并充当知识传递介质。知识管理数据库存储和管理有关在数据模型层中捕获的概念和关系的信息。它还可以支持版本管理。约束对应用程序域的语义完整性进行编码。管理委员会是选举产生的机构或委员会,负责定义和执行约束和版本管理。;部署建议的框架,我们可以更好地识别,保留软件开发人员所拥有的知识并使之制度化。这将减少人员流失对SEO的影响,为熟悉该领域或组织的软件工程师缓解陡峭的学习曲线,提供可用于事后分析的组织中知识发展的历史,并且将大大简化流程组织内部和跨组织边界的专家之间的知识了解。;我们开发了所提议框架的原型知识管理,并演示了主要需求与框架元素之间的映射。我们还将我们的方法与现有的生物信息学软件工程工具和设施进行了比较。我们在这项工作中的尝试一直是为SEO中的知识管理提供一种方法,该方法可以捕获个人创造力和团队合作精神,并同时承认集体成就的重要性和价值。

著录项

  • 作者

    Hodaei Esfahani, Keywan.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Computer Science.
  • 学位 M.Comp.Sc.
  • 年度 2008
  • 页码 131 p.
  • 总页数 131
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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