NSF Workshop on Research Data Management Implementations

University Of Chicago, Chicago IL

Investigators

Abstract

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 data are fundamental to research. While many meetings and workshops have discussed best practices, too few meetings have focused on how data management plans are implemented for different disciplines. The resulting lack of broadly applicable research data management methods and implementations has led to a culture of one-off, institution-specific, and potentially unsustainable solutions; as well as the use of data structures and formats, organizational structures, and/or metadata tagging approaches that are not maintainable or transferrable. Recommendations developed at this workshop will enable more effective coordination of data within and among institutions. This workshop will have a direct impact on the research capabilities by sharing implementations and interoperable plans for research data management. Intellectual Merit: Collecting, moving, analyzing, sharing and preserving the appropriate data are fundamental to research. While many meetings and workshops have discussed best practices, too few meetings have focused on how data management plans are implemented for different disciplines. The resulting lack of broadly applicable research data management methods and implementations has led to a culture of one-off, institution-specific, and potentially unsustainable solutions; as well as the use of data structures and formats, organizational structures, and/or metadata tagging approaches that are not maintainable or transferrable. Recommendations developed at this workshop will enable more effective coordination of data within and among institutions. This workshop will have a direct impact on the research capabilities by sharing implementations and interoperable plans for research data management.