How and why you should manage your research data: a guide for researchers
This guide provides an introduction to engaging with research data management (RDM) processes.
The guide is of interest to university researchers and research data management professional support staff. This includes any staff who give advice to researchers on the storage, management, publication and archiving of their research data.
Research data is any information that has been collected, observed, generated or created to validate original research findings. Although usually digital, research data also includes non-digital formats such as laboratory notebooks and sketchbooks.
‘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. Most of the activities should be familiar: naming files so you can find them quickly; keeping track of different versions, and deleting those not needed; backing up valuable data and outputs; 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, any research outputs or data may be used to evidence published findings, or may be combined with other data to produce new types of data record.
Effective data management is carried out for the entire lifecycle of the data, from the point of creation through to dissemination, publication and archiving. Aspects of data management will usually continue long after the initial research project has ended.
Engaging with the RDM 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)!
You can explore this further by reading our directions for research data management report, which was developed in collaboration with ARMA, SCONUL, RLUK, RUGIT and UCISA.
You can read about the main requirements and some unselfish reasons for good RDM below, but, if those don’t convince you, there are also a series of “self-interested” reasons covered in this entertaining article by Florian Markowetz.
Good RDM will benefit you and your institution by ensuring compliance with funders’ research data expectations and policies. Institutional policies may also be in place, often in response to mandates from funders.
Some funding bodies have introduced regulatory requirements. The RCUK Policy on Open Access states that “all papers must include … if applicable, a statement on how the underlying research materials – such as data, samples or models – can be accessed”. The RCUK Common Principles on Data Policy state that “publicly funded research data are a public good, produced in the public interest, which should be made openly available with as few restrictions as possible in a timely and responsible manner that does not harm intellectual property”.
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.
