Our researchers create, collect and measure large amounts of research data every day, and some of this data is used to support our internationally-recognised research. Researchers expect the University to provide secure and resilient storage during a project, on a cost-recovery basis, in order to prevent data breaches and data loss. Funders expect researchers to publish the data (and the code) which supports their findings at the end of a project unless there are ethical, commercial or public safety reasons for not doing so. In the spirit of open scholarship, researchers are expected to demonstrate they are working transparently and reproducibly. Researchers are expected to use discipline-specific file formats and metadata tags (where these exist) to improve interoperability and re-usability. Researchers are expected to document their data to improve comprehensibility for themselves and for others. Researchers studying a human population are expected to write a plan which details how they will protect and manage the personal data pertaining to their study participants. Research Data Management is concerned with all of these topics and more.
An excellent paper on Current practices in research data management and sharing in the UK has been written by Ian Carter. This is recommended reading for anyone interested in RDM today. Another outstanding paper on Good enough practices in scientific computing has been published in PLOS Computational Biology. This highly practical paper covers data management, writing code, collaborating with others, project organisation, tracking changes and writing a manuscript.