Data Management Plans: UK, US, Australia
Date: Friday, June 03
Location: 1900 Fletcher Challenge Canada Theatre, Harbour Centre
Chair: William Block
Affiliation: Cornell Institute for Social and Economic Research (CISER)
Of Policy, Practice and Tools: Data Management Planning in the Social Sciences in the UK
Presenter: Martin Donnelly
Affiliation: University of Edinburgh
Abstract:Public funders place increasing importance in data management planning (DMP) for research projects in improving the longevity of research data, and enabling widespread access and reuse. The UK's Economic and Social Research Council's new data policy continues the trend by mandating DMPs as an integral part of all research award applications. Support services have followed suit by developing tools and guidance for researchers to plan and implement data management throughout their work. The Digital Curation Centre has developed a web-based tool, DMP Online, which helps researchers develop data management plans according to their funders' requirements. The UK Data Archive, where data resulting from ESRC-funded research are archived and made available to the academic community, works closely with researchers on data sharing, providing data management guidance and advice. Ongoing efforts combine the strengths of all involved, integrating DMP Online into the ESRC application form, with UKDA and DCC providing guidance for researchers to develop strong plans - and for reviewers to evaluate these. Discussions also focus on how ESRC might monitor how plans are operationalised, and how good data management is demonstrated. In the longer term, this collaboration may provide a model for an integrated approach to DMP across all funders.
Save you time, make you famous!
Presenter: Gabrielle Gardiner
Affiliation: University of Technology Sydney
Abstract: This paper will describe the tools, resources and communication strategy designed to support researchers across multiple disciplines, to think about their data from project inception and planning through to publication and promotion. It describes a staged approach to data management planning, just-in-time information design, and tools and techniques for collaborating. This project, based at the University of Technology, Sydney was designed to improve data management planning, capture and discovery across the University as well as influence management policies and processes, but it also demonstrates the value of designing a user needs approach rather than relying on a compliance-based system. The deliverables from the project, including data management checklists and guidelines, guides to data archives, metadata approaches, protocols and tools for promotion will be discussed.
The Elements of the Data Management Plan: A Gap Analysis and Recommendations
Presenter: Amy Pienta
Affiliation: University of Michigan
Abstract: Many federal funding agencies, including NIH and most recently NSF, are requiring that grant applications contain data management plans for projects involving data collection. To support researchers in meeting this requirement, ICPSR is providing guidance on creating such plans. ICPSR published a list of elements for creating a data management plan. To determine the list of elements, ICPSR conducted a gap analysis of existing recommendations for data management plans and other forms of guidance made available for researchers generating data. The result of the gap analysis was a comparison of existing forms of guidance around the world. Findings from the gap analysis will be discussed in this presentation.
Supporting Data Management Across Disciplines
Presenter: Kathleen Fear
Affiliation: School of Information, University of Michigan
Abstract: This paper reports the results of a large-scale survey of researchers conducted in spring 2010 at the University of Michigan, aimed at understanding the variety of data management practices and concerns across disciplines. We found differences in how researchers go about managing and preserving their data and, importantly, differences in what different fields felt their most important needs for support were. For example, some groups felt a secure repository for data would be the ideal solution to their problems, while others were enthusiastic about the idea of consulting services that could help them create data management plans for particular projects. Understanding disciplinary differences in data management and the impact those differences have on the kind of support researchers need from the university is critical to implementing a successful data management program. This paper contributes to the literature on disciplinary difference in data practices and directly explores the problem of structuring services for different groups.