Introduction | Data Mgt Plan | Funder Policies | Store | Organise | Share | License | Publications | Archive
In this section:
Research data include data, records, files and other evidence on which research conclusions are based, including but 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
Funder and University requirements:
- Funders have policies 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 Edinburgh Napier University Research Data Policy must be adhered to by its researchers
Integrity of your research is improved and can be recognised:
- Research data and records are shown to be accurate, complete, authentic and reliable
- Others can use your datasets to validate your findings
- Responsible use of public resources to fund research is demonstrated
- You are supporting the responsible communication of research results
- The risk of data loss and/or data security breaches is minimised
Impact of your research:
- Reuse of your data increases its impact
- Citation of your data acknowledges your contribution
- Data may be reused by researchers in other fields for different purposes
- Data is available for discovery and re-use by yourself and others in the future
We are in the process of creating a range of introductory RDM courses for our research community which we aim to deliver in October 2015. These will be followed by specific tailored courses on ‘How to write a data management plan’ and ‘metadata and Digital Object Identifiers (DOI’s)’ later in the year.
MANTRA is a free, non-credit, self-paced course designed for postgraduate students and early career researchers which provides guidelines for good practice in research data management.
Find out how well you manage your data. Learn how to create a data management plan, securely store and share your data. MANTRA also includes practical exercises on using SPSS, NVivo, R, or ArcGIS for data handling.
You should make plans for your data before you start to create and collect it. Many funders are now asking you to do this as part of their application process. Planning at an early stage can help you make the right decisions about creating, storing and sharing your data.
Prevent loss: Data may be lost for many different reasons, from accidental file deletion to natural disasters. Even if data are not lost, they may become corrupted during storage or when transferred elsewhere. In the long term this cannot be prevented: the only way to protect against it is to ensure all files are regularly backed up and check integrity periodically.
Organise data: Keeping data safe is not enough. It is very easy for data to get disorganised quickly, making it difficult to use information which may have been gathered only a few months earlier. To avoid this you (with your colleagues on the project) should agree a structure for naming and organising your files and folders.
Having documentation of this structure (metadata – or data about your data) will help you, and others, to access, use and cite your data effectively in the long term.
Manage access: There are many reasons why you may need to restrict access to your data. It may be commercially sensitive, or contain personal information about subjects, or you may simply not be ready to publish it yet. Either way, you will need to think carefully about how you store it to prevent unauthorised users accessing it.
Equally important will be ensuring that collaborators can have access, whether they are other members of the university or external partners. Explicit consideration of data access is now a requirement for most research publications.
Write publications: Explicit consideration of access to underlying research data is now a requirement for most research publications.
Share data: It is increasingly common, especially for publicly-funded research, for data associated with a publication to themselves be published. This enables the analysis in the publication to be independently verified, demonstrating research integrity, and also creates a source of data for new types of research, such as large-scale meta-analyses.
Think about who needs access to your data; is this just colleagues at your institution or will your collaborators need access? You may need to think about protecting sensitive data from unauthorised access. Data management plans can help to manage Freedom of Information Requests (FoI) by demonstrating intent to publish in the future.
Archive data: When the project is finished you need to consider which data to deposit in a digital repository (again some funders require this). The research councils are committed to the principle that publicly funded research should be publicly accessible, and should remain so; in addition to your data you can deposit the full-text of your publications.
Long-term archival of research data is necessary to enable future use and reuse, both by the originating researchers and (where applicable) by others.
We gratefully acknowledge the work of the University of Bath in the development of this guidance.
Introduction| Data Mgt Plan | Funder Policies | Store | Organise | Share | License | Publications | Archive