Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Help LibGuides

Research Data Management: Core principles

For enquiries, please use the appropriate address from the University of Hull Key Contacts list.

What am I trying to achieve?

Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical)UKRI Concordat on Open Research Data, 2016.


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.

Visualisation of the data lifecycle


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.

newSee 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.

What counts as 'data'?

image of a pile of papersRDM 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 Data

logo for the open data movementOpen 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.

In 2016, an international collective of researchers published the FAIR Principles for data management:  acknowledging that the dissemination of STEM data is usually computer-driven, datasets must be FindableAccessibleInter-operable and Re-usable.

The international GO FAIR initiative works to implement these principles with stakeholders at all levels, with funding from several European ministries of science.

logo for the GoFair movement


Who owns my data?

CREATe logoA 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.