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.
Cite
@article{arxiv.1208.3754,
title = {DMP Planning for Big Science Projects},
author = {Juan Bicarregui and Norman Gray and Rob Henderson and Roger Jones and Simon Lambert and Brian Matthews},
journal= {arXiv preprint arXiv:1208.3754},
year = {2012}
}
Comments
Project final report, 47 pages; see http://purl.org/nxg/projects/mardi-gross/report for other document versions