The significance of research data and developing methods to manage their ever-increasing quantities is a common issue amongst researchers. Reproducibility or the ability for another researcher to replicate analyses to validate theories and produce complementary or entirely new science is essential.
As science is increasingly based on computation, there is a correlation in the importance of making data and code accessible for significant scientific impact. Therefore, researchers should aim to make their research data FAIR (Findable, Accessible, Interoperable / Intelligible, Reusable); that is:
Findable: assigning a persistent identifier and having rich metadata
Accessible: keeping data open using a standardised protocol
Interoperable/Intelligible: using community agreed formats, languages and vocabularies
Reusable: data should maintain its initial richness
To assist* researchers, the following data management guidelines have been developed for Pawsey Supercomputing Centre users, respective to its partner institutions:
CSIRO Research Data Management Home
Curtin University Research Data Management
Edith Cowan University Research Data Management
Murdoch University Research Data Management
University of Western Australia Research Data Management
*We also acknowledge the support of ANDS (Australian National Data Service) in reviewing documentation and providing some of the content. These guides are accurate as of 21 January 2015.
The Pawsey Supercomputing Centre research data management guides are intended for general advice only – if you have any questions, please contact firstname.lastname@example.org.
Checklists for Data Management
The following checklists and documentation have been put in place to guide users with their data management:
It is recommended that these guides are reviewed prior to data use at the Pawsey Supercomputing Centre.