DMP Planning for Big Science Projects
Juan Bicarregui, Norman Gray, Rob Henderson, Roger Jones and, Simon Lambert, Brian Matthews

TL;DR
This paper offers strategic guidance for developing Data Management and Preservation plans tailored to 'Big Science' projects, emphasizing high-level planning aligned with the OAIS model.
Contribution
It provides a high-level framework and best practices for planning data management and preservation in large-scale scientific projects, tailored to organizations with sufficient resources.
Findings
Guidance aligned with OAIS reference model
Framework adaptable to various 'Big Science' projects
Emphasis on high-level strategic planning
Abstract
This report exists to provide high-level guidance for the strategic and engineering development of Data Management and Preservation plans for 'Big Science' data. Although the report's nominal audience is therefore rather narrow, we intend the document to be of use to other planners and data architects who wish to implement good practice in this area. For the purposes of this report, we presume that the reader is broadly persuaded (by external fiat if nothing else) of the need to preserve research data appropriately, and that they have both sophisticated technical support and the budget to support developments. The goal of the document is not to provide mechanically applicable recipes, but to allow the user to develop and lead a high-level plan which is appropriate to their organisation. Throughout, the report is informed where appropriate by the OAIS reference model.
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Taxonomy
TopicsResearch Data Management Practices · Advanced Data Storage Technologies · Scientific Computing and Data Management
