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Research data

  • Definition

    Research data includes data, records, files and other evidence on which research conclusions are based. The simplest way of defining Research Data is as material that supports your research output.

  • Examples

    Research data include but is not limited to:

    • Results of experiments or simulations
    • Statistics and measurements
    • Models and software
    • Observations e.g. fieldwork
    • Survey results – print or online
    • Interview recordings and transcripts, and coding applied to these
    • Images, from cameras and scientific equipment
    • Textual source materials and annotations
    • Physical artefacts and samples.
  • Benefits

    There are many benefits to good data management. Below are the most common:

    Meet funder requirements:

    • Most funders have a policy on the management of research data which must be complied with
    • Industrial collaborators may have different practices with which you will need to comply

    The integrity of your research is improved and can be recognised:

    • Research data and records are accurate, complete, authentic and reliable
    • Data security is improved and the risk of data loss minimised
    • Providing access to your datasets enables others to validate your findings
    • Responsible use of public resources to fund research is demonstrated
    • It supports the responsible communication of research results

    Increase the impact of your research:

    Support future use:

  • Fair Data Guiding Principles

    The FAIR Guiding Principles

    To be Findable:

    F1. (meta)data are assigned a globally unique and persistent identifier 
    F2. data are described with rich metadata (defined by R1 below) 
    F3. metadata clearly and explicitly include the identifier of the data it describes 
    F4. (meta)data are registered or indexed in a searchable resource

    To be Accessible:

    A1. (meta)data are retrievable by their identifier using a standardised communications protocol 
    A1.1 the protocol is open, free, and universally implementable 
    A1.2 the protocol allows for an authentication and authorisation procedure, where necessary 
    A2. metadata are accessible, even when the data are no longer available

    To be Interoperable:

    I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation 
    I2. (meta)data use vocabularies that follow FAIR principles 
    I3. (meta)data include qualified references to other (meta) data

    To be Reusable:

    R1. meta(data) are richly described with a plurality of accurate and relevant attributes 
    R1.1. (meta)data are released with a clear and accessible data usage license 
    R1.2. (meta)data are associated with detailed provenance 
    R1.3. (meta)data meet domain-relevant community standards

Get in touch

If you have any questions about using our services, please contact us using one of the following email addresses:

Research Data Management queries: researchdatamanagement@stir.ac.uk

 

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