Subject Guides: Research Data Management: An overview

Research Data

“If I have seen further, it is by standing upon the shoulders of giants.” Sir Isaac Newton 1675

"Data", or "Research data" are regarded as the primary unit of any research enquiry. Data are collected to identify patterns in the field that support a particular theory or hypothesis. Data can be collected using a variety of methods and can take a wide variety of formats. Quantitative data may be numerical such as temperature taken over a specified period of time. Qualitative data can be a series of field notes, anecdotes, photographs or recorded audio and/or video interviews or clips concerning particular events or experiments.

While data may have been collected to address a particular research question, it may also answer different questions or prompt new questions for further research, either in the same field or a completely different one.

While research projects have their own lifespan, research data can have a life beyond its' original project. Managing your research data during collection, storage, analysis, publication and making provision for access to it after the conclusion of your project is crucial to the scientific community.

Useful Tools & Resources

Open Data defined

Why share research data?

Data sharing has become a mandatory requirement by institutions, funders and publishers.

Benefits of data sharing with research colleagues and communities include:

- Promotes new discoveries

- Increases research impact

- Supports validation and replication

- Enhances collaboration

- Return on public investment

- Reduced redundant research

F.A.I.R. Data Principles

Sharing data ensures that other researchers can access and use your data for further study. The FAIR data principles address the sharing of data by providing the following guidelines:

Findable: The research data record need to be discoverable by other researchers. Applying the appropriate description using general or subject specific metadata allows researchers to discover your data.

Accessible: Your data needs to be stored for the long term in an recognised storage facility such as a data repository. The data needs to be freely accessible and downloadable and useable.

Interoperable: Data and metadata needs to be written in a format that is accessible and can be interpreted by researchers and integrated with other data for analysis and processing.

Re-useable: The goal is the optimum re-use of data. Data needs to be fully described in as much detail as possible including its provenance and using community or subject specific standards.

F.A.I.R. principles apply to three aspects; the data (digital object), the metadata (a description of that object) and the infrastructure / repository where the data is stored and from which it is shared or accessed.