Data created from research are valuable resources that can be used and reused for future scientific and educational purposes.
Good data management practices are essential in research, to make sure that research data are of high quality, are well organised, documented, preserved and accessible and their validity controlled at all times. Well-managed data are easily shared and can thus be used for new research or to duplicate and validate existing research.
Research Data Management (RDM) needs to be planned early in a project (or beforehand), so that practices can be implemented throughout the research cycle.
RDM is not just for scientists! Research 'data' (or 'material') comes in many forms. For instance:
| Diaries | Audio recordings and transcripts | Lab/field notebooks |
| Search histories | Photographs and videos | Source code |
| Bibliographies | Survey responses | Specimens and samples |
| Quotations | Test results | Models |
Open access to the data underlying research findings is essential component of Open Research: "the idea that... knowledge of all kinds should be openly shared as early as it is practical in the discovery process”. (Michael Nielsen, one of the leading advocates of the Open Research movement).
Open access to research data demonstrates academic integrity, supports reproducibility, increases opportunities for impact, and contributes to public engagement.
Even sensitive data which cannot be shared openly can be managed according to Open Research principles: register your study, make a public statement about the nature of your data, and invite people to contact you for further information.
A series of highly readable pdf guides originating from CREATe, the UK Copyright and Creative Economy Centre at the University of Glasgow:
See also How To Licence Research Data, from Edinburgh's Digital Curation Centre (2014), for a comprehensive overview of suitable licence types for datasets.
