What is Research Data Management (RDM?)
Research Data Management is the organisation, documentation, storage, and preservation of the data you collect, create or use during your research.
It is a systematic, consistent and structured approach to ensure that research is findable, accessible, interoperable, and reusable (FAIR). At it's core Research Data Management is simply good research practice. Responsibly managed data is important for research integrity, transparency and open research.
Research Data Management is crucial throughout the research lifecycle
Managing research data is critical at every stage of your research process:
- Planning your research: Preparing a Data Management Plan, Adequately costing for data management, gaining ethical approval, preparing data sharing agreements/IPR.
- Performing your research: Collecting data, implementing ethics methods.
- Managing and analysing your results: formatting and documenting data, securing data, storing data.
- Archiving and sharing data: Selecting data to retain, storing unpublished data, depositing data in a data repository, selecting an open licence, writing a data access statement.
- Data Disposal.
What is Research Data?
The concept of data can seem science-focused, but it is equally relevant to arts, humanities, and social sciences.
The Concordat on Open Research Data defines research data as:
Data is evidence
The evidence that underpins the answer to the research questions and can be used to validate findings regardless of its form (e.g. print, digital, or physical). Data might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence.
Data may be raw or primary (e.g. direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (e.g. cleaned up or as an extract from a larger data set) or derived from existing sources where the rights may be held by others. Data may be defined as 'relational' or 'functional' components of research, thus signaling that their identification and value lies in whether and how researchers use them as evidence for claims.
Researchers of all disciplines use research data
Research data can come from different sources, take different mediums and have many different forms.
Data includes, for example, archival documents, museum objects, audio files, AV material, images, transcripts, field notes, text corpus, statistics, models, software, spreadsheets and log files.
What do I gain from responsibly managing my research data?
Managing your research data makes it easier to:
- write up papers and theses using data recorded and documented consistently throughout a project
- continue using data after the researcher responsible has left the university
- choose data for long-term archival and for disposal to save space
Managing your research data helps prevent:
- loss of data
- inability to prove research findings
- costly repetition of data collection
- accidental breaches of privacy and ethical legislation
- inability to support commercialisation of research outcomes
- Good research data management makes it easier to fulfil the commitments of responsible research by making it repeatable, reproducible, replicable and reusable.
- Being confident in the rigour, robustness and completeness of your data now will allow future research to be built on solid foundations.
For the individual academic, well-managed data can be shared with confidence, leading to:
- additional citations of both papers and datasets
- demonstrable impact through commercial use of data
- unanticipated insights from new techniques and combination of datasets
For the above reasons research funders and publishers, as well as Ulster University, all have policies that require data to be managed properly.
