Scientific Data Management – the management of storage, access, usage, lifecycle, content, and meaning for scientific data – and the collaborative sharing of it, is not as commonly employed in computational science as it is in other fields. However, where these have been co-developed and in particular tightly integrated with the computational science research process, they have had a transformational influence on scientists’ work processes. These efforts enabled not only new and previously impossible research, but also helped to speed up research processes and improve research output. This chapter describes the key principles and components of a good data management system, provides real world examples of how these can be successfully integrated with scientific research processes and enable successful data sharing, provides an outlook on future developments, and discusses lessons learned. We conclude with a short section on how to get started for those whose interest has been piqued.
|Translated title of the contribution||Integrating Data Management and Collaborative Sharing with Computational Science Research Processes|
|Title of host publication||Handbook of Research on Computational Science and Engineering: Theory and Practice|
|Editors||J. Leng, Wes Sharrock|
|Pages||506 - 538|
|Number of pages||33|
|Publication status||Published - 2011|