NSF Workshop on Research Data Management Implementations

本次研讨会的目的是将研究人员聚集在一起，讨论实际的数据管理实施架构及其在特定学科工作流程中的应用。因此，本次研讨会建立在2011年在普林斯顿大学举行的NSF资助的数据生命周期管理研讨会的成果之上，将重点转移到实施解决方案上。我们将邀请提交职位和经验论文，描述基于学科的数据管理基础设施和服务的实施，以及这些解决方案利用机构内外资源的方式。研讨会还将邀请与会者讨论研究计算中心之间的协调努力如何加速有效的研究数据管理工作流程的实施，并为国家的努力和倡议做出贡献。知识价值：收集，移动，分析，共享和保存适当的数据是研究的基础。虽然许多会议和研讨会都讨论了最佳实践，但很少有会议关注如何为不同学科实施数据管理计划。由此造成的缺乏广泛适用的研究数据管理方法和实施，导致了一种一次性的，机构特定的，潜在的不可持续的解决方案的文化;以及使用的数据结构和格式，organizationalstructures，和/或元数据标记方法，是不可维护或transferable.Recommendations在本次研讨会上制定的将使数据更有效的协调机构内和机构之间。本次研讨会将通过分享研究数据管理的实施和互操作计划对研究能力产生直接影响。智力优势：收集、移动、分析、共享和保存适当的数据是研究的基础。虽然许多会议和研讨会都讨论了最佳实践，但很少有会议关注如何为不同学科实施数据管理计划。由此造成的缺乏广泛适用的研究数据管理方法和实施，导致了一种一次性的，机构特定的，潜在的不可持续的解决方案的文化;以及使用的数据结构和格式，organizationalstructures，和/或元数据标记方法，是不可维护或transferable.Recommendations在本次研讨会上制定的将使数据更有效的协调机构内和机构之间。该研讨会将通过分享研究数据管理的实施和互操作计划，对研究能力产生直接影响。

The objective of this workshop is to bring together researchers to discuss actual data management implementation architectures and their application to discipline-specific workflows. This workshop thus builds on the results of the NSF funded data lifecycle management workshop held at Princeton University in 2011, shifting focus to implementations solutions. We will invite submission of position and experience papers that describe implementations of discipline-based data management infrastructure and services, and the ways in which those solutions leverage resources within and outside their institutions. The workshop will also engage participants in a discussion of how a coordinated effort among research computing centers may accelerate the implementation of effective research data management workflows, and contribute to national efforts and initiatives.Intellectual Merit: Collecting, moving, analyzing, sharing and preserving the appropriate dataare fundamental to research. While many meetings and workshops have discussed bestpractices, too few meetings have focused on how data management plans are implemented fordifferent disciplines. The resulting lack of broadly applicable research data managementmethods and implementations has led to a culture of one-off, institution-specific, and potentiallyunsustainable solutions; as well as the use of data structures and formats, organizationalstructures, and/or metadata tagging approaches that are not maintainable or transferrable.Recommendations developed at this workshop will enable more effective coordination of datawithin and among institutions. This workshop will have a direct impact on the researchcapabilities by sharing implementations and interoperable plans for research data management.Intellectual Merit: Collecting, moving, analyzing, sharing and preserving the appropriate dataare fundamental to research. While many meetings and workshops have discussed bestpractices, too few meetings have focused on how data management plans are implemented fordifferent disciplines. The resulting lack of broadly applicable research data managementmethods and implementations has led to a culture of one-off, institution-specific, and potentiallyunsustainable solutions; as well as the use of data structures and formats, organizationalstructures, and/or metadata tagging approaches that are not maintainable or transferrable.Recommendations developed at this workshop will enable more effective coordination of datawithin and among institutions. This workshop will have a direct impact on the researchcapabilities by sharing implementations and interoperable plans for research data management.