Data-Driven knowledge mobilization, translation and innovation

数据驱动的知识动员、转化和创新

• 批准号: 478840-2015
• 负责人: Lyons, Kelly
• 金额: $ 18.14万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=579817
• 关键词: Data; Driven; knowledge; mobilization; translation

Knowledge workers comprise a large proportion of the workforce today working in the context of large-scale expert networks, spanning across different disciplines and organizations. They rely on software technologies for their discipline-specific activities and for their coordination and their communication with each other. This type of networked, interdisciplinary knowledge work is motivated by a belief that the complex problems of our time can only be effectively addressed through broad collaborations of experts and partners who act both as knowledge generators and receptors to create value through new products and services. However, even as this belief is generally, and increasingly shared, the question of "how these networks can be supported to become more effective" is still very much open and the subject of considerable debate. The goal of our proposed research is to develop methods and tools for analyzing and enhancing the data sets through which knowledge workers collaborate, our hypothesis being that, by doing so, we can effectively amplify their productivity. These methods and tools will be validated through case studies with our partner organizations: an enterprise research and development (R&D) organization (within Dell Computers) and two Canadian research networks (the AGE-WELL and GlycoNET NCEs). We will demonstrate how our tools can enhance innovation productivity and help mobilize the work products of our partners towards adoption and value creation. Our goal is to: understand, support and improve the end-to-end process of (a) bringing the right individuals together, (b) collaborating and contributing their complementary expertise, and (c) making use of supporting processes and practices to create value through innovation in products and services. Within enterprise R&D organizations, our results will enable more people to be involved in the innovation process and will increase the number, quality and pace of ideas developed and disclosed. Within NCEs, our results will advance our understanding of the operating parameters of effective knowledge mobilization, translation and value creation and improve monitoring, reporting, evaluating, accountability and transparency in research networks.

知识工作者构成了当今在跨越不同学科和组织的大规模专家网络中工作的劳动力的很大一部分。他们依靠软件技术进行特定学科的活动，以及他们的协调和相互沟通。这种联网的跨学科知识工作的动机是相信，我们这个时代的复杂问题只能通过专家和合作伙伴的广泛合作来有效解决，他们既是知识的产生者，也是知识的接受者，通过新产品和服务创造价值。然而，尽管这一信念已得到普遍认同，而且越来越多地得到认同，但“如何支持这些网络使其更加有效”的问题仍然是一个悬而未决的问题，也是一个引起大量辩论的主题。我们提出的研究的目标是开发分析和增强知识工作者合作的数据集的方法和工具，我们的假设是，通过这样做，我们可以有效地提高他们的生产力。这些方法和工具将通过与我们的合作伙伴组织的案例研究进行验证：一个企业研究和开发（R&D）组织（在戴尔计算机内部）和两个加拿大研究网络（AGE-WELL和GlycoNET NCE）。我们将展示我们的工具如何提高创新生产力，并帮助调动我们合作伙伴的工作产品，以实现采用和价值创造。我们的目标是：理解、支持和改进端到端流程：（a）将合适的人员聚集在一起，（B）合作并贡献互补的专业知识，以及（c）利用支持流程和实践，通过产品和服务创新创造价值。在企业研发组织中，我们的成果将使更多的人参与创新过程，并将提高开发和披露的想法的数量、质量和速度。在NCEs中，我们的研究结果将促进我们对有效知识动员，转化和价值创造的操作参数的理解，并改善研究网络的监测，报告，评估，问责制和透明度。