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现架构及其在特定学科工作流程中的应用。因此，本次研讨会以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为基础，将重点转移到实现解决方案上。我们将邀请提交立场和经验论文，描述基于学科的数据管理基础设施和服务的实现，以及这些解决方案利用其机构内外资源的方式。讲习班还将使与会者参与讨论研究计算中心之间的协调努力如何加速实施有效的研究数据管理工作流程，并促进国家的努力和倡议。智力价值：收集、移动、分析、共享和保存对研究至关重要的适当数据。虽然许多会议和研讨会讨论了最佳实践，但很少有会议关注如何针对不同学科实施数据管理计划。因此，缺乏广泛适用的研究数据管理方法和实施，导致了一次性、特定机构和潜在不可持续的解决方案的文化；以及不可维护或不可转移的数据结构和格式、组织结构和/或元数据标记方法的使用。本次讲习班提出的建议将使各机构内部和机构之间的数据协调更加有效。本次研讨会将通过分享研究数据管理的实现和互操作计划，对研究能力产生直接影响。智力价值：收集、移动、分析、共享和保存对研究至关重要的适当数据。虽然许多会议和研讨会讨论了最佳实践，但很少有会议关注如何针对不同学科实施数据管理计划。因此，缺乏广泛适用的研究数据管理方法和实施，导致了一次性、特定机构和潜在不可持续的解决方案的文化；以及不可维护或不可转移的数据结构和格式、组织结构和/或元数据标记方法的使用。本次讲习班提出的建议将使各机构内部和机构之间的数据协调更加有效。本次研讨会将通过分享研究数据管理的实现和互操作计划，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.