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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.
This text and graphic has been adapted from the UK Data Service's training materials for 'Preparing and Managing Data'. The UK Data Service is funded by the Economic and Social Research Council (ESRC) to meet the data needs of researchers, students and teachers from all sectors.
See also: A Guide to Research Data Management (2021), from the British Library - a concise overview of core principles for beginners, with key terms explained in plain English.
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.
The international GO FAIR initiative works to implement these principles with stakeholders at all levels, with funding from several European ministries of science.
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.
