This guide provides an introduction to engaging with research data management processes.
It will be of interest to university researchers and research data management support staff, including those who are responsible for giving advice to researchers on the storage, management, publication and archiving of research data.
What is research data management?
'Research data management' is simply the effective handling of information that is created in the course of research.
Managing research data is usually an integral part of the research process, so you probably already do it. This is demonstrated further by the familiarity of most of the activities involved: naming files so you can find them quickly; keeping track of different versions, and deleting those not needed; backing up valuable data and controlling who has access to your data.
How research data is handled depends on the type of data involved, how that data is created or collected and how the data is to be used now and in future. For example, most data from experiments is reproducible; other data may not be repeatable, such as observations from the field.
However, both types may be used to evidence published findings, or may be combined with other data to produce new types of data record.
Effective data management extends over the entire lifecycle of the data, from the point of creation through to dissemination, publication and archiving, and will usually continue long after the initial research project has concluded.
Why should I manage my research data?
Engaging with the research data management process at your institution can provide benefits for you as well as your students, other researchers, your institution, and your external collaborators and partners.
Your research data is crucial as it is the evidence base for your research findings. Your research data is also a valuable resource that will have taken a great deal of time and money to create.
There are a number of very good reasons why research data should be managed in an appropriate and timely manner and they are associated with the reasons for sharing data. These could be seen as both sticks (requirements) and carrots (benefits)!
Research data management requirements (the sticks)
Compliance with policies
Your institution needs to ensure compliance with both funders’ and institutional research data expectations and policies.
Some funding bodies have introduced regulatory requirements, and all funders around the world are taking more interest in the outputs of research. Most funders now require the production of a data management plan (DMP). DMPOnline has been developed by the Digital Curation Centre (DCC) to help you write data management plans. It has templates for all funders, and guidance (where available) from your institution.
We have also published a guide, meeting the requirements of the EPSRC research data policy, which suggests approaches to research data management that will enable universities to meet the requirements of the EPSRC policy framework on research data concerning the management and provision of access to EPSRC-funded research data.
Ensure your data is accessible and shareable
While we are on the subject of compliance, journal publishers increasingly require data that form the basis for publications to be shared or deposited in an accessible data centre or repository. This requirement can apply to both commercially and publicly-funded research.
A Jisc/Research Libraries UK (RLUK) service, SHERPA JULIET, lists open access publishing and data archiving policies. We are currently funding the development of the UK Research Data Discovery Service, which will aggregate metadata for research data held within UK universities and national, discipline specific data centres to help ensure increased access to data.
Dependent on your discipline, it would also be worth checking The Public Library of Science (PLOS) data policy, linked from this explanatory blog post.
With regards to other developments in the EU, FOSTER, (Facilitate Open Science Training for European Research) is a two-year, EU-funded (FP7) project, carried out by 13 partners across eight countries. The primary aim is to produce a European-wide training programme that will help researchers, postgraduate students, librarians and other stakeholders to incorporate open access approaches into their existing research methodologies.
Demonstrate responsible practice
By managing your research data and making it publicly available you will be able to demonstrate the responsible use of public resources to fund research. It’s worth remembering that Research Excellence Framework (REF) 2014 permitted the submission of research outputs in any form providing they embodied original research; it is likely this will be the same in REF 2020.
Research funders are considering ways to recognise data more formally in assessments but accept this needs to be manageable.
The DCC also has some guidance on freedom of information requests.
What are the benefits (the carrots)?
The Knowledge Exchange gathered evidence, examples and opinions on current and future incentives for research data sharing from the researchers’ point of view in five EU countries, in order to provide recommendations for policy and practice development on how best to incentivise data access and re-use. Read the findings in incentives and motivations for sharing research data, a researcher’s perspective.
Keep your research safe and secure
You can reduce the risk of data loss by keeping your research data safe and secure: use of robust and appropriate data storage facilities will help to reduce the loss of your data through accidents, or neglect. Making it clear what your needs are to your institution will help them put in place adequate storage facilities for your data.
The right place for your research data is most likely to be your institution’s own data repository or possibly a disciplinary repository (you can work out which by seeking advice from your local library or using an extensive list on the re3data.org registry of research data repositories).
Increase your research efficiency
You can increase your research efficiency: good research data management will enable you to organise your files and data for access and analysis without difficulty. This way you can track progress more easily, and mitigate against the risk of a team member leaving taking valuable knowledge about the nature and extent of work completed with them.
Improve your research integrity
Good data management can result in improved research integrity as well as act as validation for research results. Accurate and complete research data are an essential part of the evidence necessary for evaluating and validating research results and for reconstructing the events and processes leading to them.
Make your research outputs more visible
Making your data available enhances the visibility of your research outputs and increases the number of citations. Research data, if correctly formatted, described and attributed, will have significant ongoing value and can continue to have impact long after the completion of a research project. A “robust citation benefit from open data” was found by Piwowar and Vision (2013).
Perhaps the most common reasons to retain and manage research data are to ensure reproducibility and to facilitate online sharing.
Data citation underpins the recognition of data as a primary research output rather than as a by-product of research. There are a number of data citation initiatives, including DataCite, a registry assigning unique digital object identifiers (DOIs) to research data. Using a DOI helps to make data citable, traceable and findable, so that research data, as well as publications based on those data, can form an alternative, but important part of a researcher's output.
We are currently collaborating with the British Library to promote the use of persistent identifiers.
A DOI is also short and easy to share on social media.
You could be providing opportunities for collaboration with other researchers within your discipline, or even with other disciplines, by facilitating the sharing and re-use of research data for future research.
Good research data management will permit new and innovative research to be built on existing information, hence the importance of research data quality and provenance. Sharing well-managed research data and enabling others to use it will also help to prevent duplication of effort.
It follows that if you work in a relevant area then you may like to consider the impact of data-driven research,
“small studies may cumulate into larger endeavours; in that case, the data from each individual study may become more valuable as the data cumulate, enabling comparisons across time periods and locations”
Advanced computing capabilities help researchers manipulate and explore massive datasets, an idea that’s articulated as The Fourth Paradigm of discovery based on data-intensive science.
How to get started
As both the creators and users of research data, researchers are crucial in the development of research data management and data sharing services.
Overall, by managing your data well, and fitting within the policies and frameworks you are required to, you could increase debate and the potential for new enquiry in your field, ensure that you continue to receive funding, and make yourself open to innovation and potential new data uses.
There are some excellent training programmes available online, mostly originating from Jisc funding, for example:
- Mantra - a free online course designed for researchers or others who manage digital data as part of a research project
- TraD - includes a blended learning course for those in (or expecting to be in) research data management support roles
- RDMRose - an open educational resource for information professionals on research data management
Working with your institution
Your institution needs to closely understand your research, its patterns and timetables, motivations and priorities, to put in place a supportive infrastructure. University management should define expectations and support staff will deliver services.
As a researcher and primary data creator you can:
- Manage your data appropriately within your institutional policy and the guidelines set out locally or for your discipline; the main way you can do this is by creating a data management plan at the outset and revisit it on a regular basis
- Make sure you clearly articulate - in terms of the data creation, use and management - the requirements, opportunities and obstacles you might encounter while doing your research
- Use your institutional repository, or an appropriate disciplinary repository for storing your data and publications
Our research at risk co-design area is an overarching theme for the range of work Jisc is delivering to help universities and others address the urgent challenges involved in sharing and managing research data.