研究网络系统:旨在增强转化研究基础设施的机构采用状况。

Journal of translational medicine & epidemiology Pub Date : 2014-01-01 Epub Date: 2014-08-02
Jihad S Obeid, Layne M Johnson, Sarah Stallings, David Eichmann
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引用次数: 0

摘要

随着对转化研究的日益重视,促进跨机构内部和跨机构边界的多学科合作变得越来越重要。因此,促进发现潜在合作者的研究网络系统受到了旨在增强其研究基础设施的机构的极大关注。我们进行了一项调查,以评估临床和转化科学奖(CTSA)资助机构采用这些新工具的情况。调查结果表明,大多数CTSA资助的机构要么已经采用,要么正在计划采用几种可用的研究联网系统之一。此外,许多这样的机构已经公开或计划公开使用链接开放数据(一种已建立的语义web服务方法)的研究专业知识数据。对这些公开数据的初步探索表明,这些数据在评估跨机构合作方面有很大的用处。然而,在了解和衡量这些技术对跨机构研究合作的影响之前,需要进一步采用这些技术并对数据进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Research Networking Systems: The State of Adoption at Institutions Aiming to Augment Translational Research Infrastructure.

Research Networking Systems: The State of Adoption at Institutions Aiming to Augment Translational Research Infrastructure.

Research Networking Systems: The State of Adoption at Institutions Aiming to Augment Translational Research Infrastructure.

Research Networking Systems: The State of Adoption at Institutions Aiming to Augment Translational Research Infrastructure.

Fostering collaborations across multiple disciplines within and across institutional boundaries is becoming increasingly important with the growing emphasis on translational research. As a result, Research Networking Systems that facilitate discovery of potential collaborators have received significant attention by institutions aiming to augment their research infrastructure. We have conducted a survey to assess the state of adoption of these new tools at the Clinical and Translational Science Award (CTSA) funded institutions. Survey results demonstrate that most CTSA funded institutions have either already adopted or were planning to adopt one of several available research networking systems. Moreover a good number of these institutions have exposed or plan to expose the data on research expertise using linked open data, an established approach to semantic web services. Preliminary exploration of these publically-available data shows promising utility in assessing cross-institutional collaborations. Further adoption of these technologies and analysis of the data are needed, however, before their impact on cross-institutional collaboration in research can be appreciated and measured.

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