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Persistent URL http://purl.org/net/epubs/work/64381
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Record Id 64381
Title Data Management and Preservation Planning for Big Science
Abstract "Big Science" - that is, science which involves large collaborations with dedicated facilities, and involving large data volumes and multinational investments - is often seen as different when it comes to considering data management and preservation planning. Big Science handles its data differently from other disciplines and has data-management problems which are qualitatively different from other disciplines. These differences arise in part from the quantities of data, of course, but possibly more importantly from the cultural, organisational and technical distinctiveness of these academic cultures. Consequently, the data management systems are typically and rationally bespoke, but this means that the planning for data management and preservation (DMP) must be bespoke, too. These differences are such that "just read and implement the OAIS spec" is reasonable Data Management and Preservation (DMP) advice, but this bald prescription can and should be usefully supported by a methodological "toolkit", including overviews, case-studies and costing models to provide guidance on developing best practise in DMP policy and infrastructure for these projects, as well as considering OAIS validation, audit and cost modelling. In this paper, we build on previous work with the LIGO collaboration, to consider the role of data and preservation planning within these big science scenarios, and discuss how to apply current best practice in DMP. We discuss the result of the MaRDI-Gross project (Managing Research Data Infrastructures ? Big science), which has been developing a toolkit to provide guidelines on the application of best practice in data management and preservation planning within big science projects. This is targeted primarily at projects, engineering managers, but intending also to help funders collaborate on DMP plans which satisfy the requirements imposed on them.
Organisation STFC , SCI-COMP , SCI-COMP-SI
Keywords DMP policy , data preservation , DMP , digital curation , data management
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Language English (EN)
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Paper In Conference Proceedings In 8th International Digital Curation Conference (IDCC13), Amsterdam, NL, 16-17 Jan 2013, (2013). IDCC8-MardiGross-final.pdf
Journal Article The International Journal of Digital Curation 8, no. 1 (2013): 29-41. doi:10.2218/ijdc.v8i1.247 2013