Data management plan
From April 2011, ESRC grant applicants who plan to generate data should prepare and submit a data management plan
for their research project as part of the grant application, in the form of an attachment to the Je-S form.
For information about and examples of data management plans for social and economic data, see:
- Rural Economy and Land Use Programme (Relu) data management planning - Relu researchers have been preparing similar data management plans since 2004
A data management plan is an opportunity to consider and describe, when research is being designed and planned, how
the research data are going to be managed throughout the research cycle and shared afterwards (by archiving via the Economic and Social Data Service).
Research data generated by ESRC-funded research must be well-managed by the award holder during the award period to enable their data
to be exploited to the maximum potential for further research. Most data generated as a result of economic and social research can be successfully archived and shared.
Some research data are more sensitive than others. It is a responsibility of the award holders to consider all issues related
to confidentiality, ethics, security and copyright before initiating the research. Any challenges to data sharing (e.g. copyright or data
confidentiality) should be critically considered in a plan, with possible solutions discussed to optimise data sharing.
A data management plan should include:
- assessment of existing data
- information on new data
- quality assurance of data
- back-up and security of data
- expected difficulties in data sharing
- copyright/Intellectual Property Right
- responsibilities
- preparation of data for sharing and archiving
Assessment of existing data
When creating new data sources, explain why existing data sources can not be re-used. If purchasing or re-using existing data
sources, explain whether issues such as copyright and IPR have been addressed to ensure that the data can be shared i.e. explain
how you plan to deal with permissions to share data you have created which is derived from data which you do not own.
The following sources can be reviewed for the availability of existing data that could be used:
-
ESDS Data Catalogue
- an integrated catalogue containing over 5,000 datasets covering an extensive
range of key economic, social and historical data - both quantitative and
qualitative - spanning many disciplines and themes, and with links to census
data
-
ESRC Research Catalogue - the ESRC's repository
of past and present research awards and their outputs
Information on new data
Give a brief description of new data which you envisage creating. This information should include how the data
will be collected (in line with the proposed research methods), their format (e.g. SPSS, Open Document Format, tab-delimited format, MS Excel),
and how they will be documented.
Using standardised and interchangeable or open lossless data formats ensures the long-term usability of data. Clear and detailed data
descriptions and annotation, together with user-friendly accompanying documentation on methods and contextual information, makes data easy
to understand and interpret and therefore shareable and with long-lasting usability.
Quality assurance of data
Quality control of data is an integral part of a research process. Describe the procedures for quality assurance that will be carried out on the
data collected at the time of data collection, data entry, digitisation and data checking.
For example this might include:
- documenting the calibration of instruments
- taking duplicate samples or measurements
- standardised data capture, data entry or recording methods
- data entry validation techniques
- methods of transcription
- peer review of data
See:
Back-up and security of data
Describe the data back-up procedures that you will adopt to ensure the data and metadata are securely stored during
the lifetime of the project. You may need to discuss your institution's policy on back-ups. If your data is sensitive (e.g.
detailed personal data) you should discuss appropriate security measures which you will be taking.
The methods of version control of data files should also be stated. Version control includes making sure that if the information in one file is altered, the related information in
other files is also adapted, as well as keeping track of versions of data files and their locations.
Expected difficulties in data sharing
If you expect any obstacles to sharing your newly generated data explain their causes and possible measures you are
going to apply to overcome them. If you consider that there will be ethical issues which may cause difficulties in data
sharing explain your strategies for dealing with these issues in the relevant section of the Je-S form, e.g. where possible
discussing archiving with interviewees or anonymising data. Refer to the requirements of the ESRC Framework for Research Ethics.
Research data - even sensitive and confidential data - can be shared ethically and legally if you pay attention,
from the beginning of research, to three important aspects:
- when gaining informed consent, include provision for data sharing
- where needed, protect people’s identities by anonymising data
- consider controlling access to data
For detailed guidance see:
Copyright/Intellectual Property Right
State who will own the copyright and IPR of any new data that you will generate.
Responsibilities
Indicate who within your research team will be responsible for data management, metadata production,
dealing with quality issues and the final delivery of data for sharing or archiving. Provide this information
within the Staff Duties section in the Je-S form and where appropriate in the Justification of Resources. If several
people will be responsible state their roles and responsibilities in the relevant section of the Je-S form.
For collaborative projects you should explain the co-ordination of data management responsibilities across partners
in your Data Management Plan.
Preparation of data for sharing and archiving
Outline your plans for preparing and documenting data for sharing and archiving with the ESDS (unless otherwise agreed).
Identify any additional plans for data sharing, if any. A crucial part of making data user-friendly, shareable and with long-lasting
usability is to ensure they can be understood and interpreted by other users. This requires clear and detailed data description,
annotation and contextual information.
If you have a specific query relating to data management planning for your ESRC application or award, please contact acquisitions@esds.ac.uk
or telephone 01206 872974.
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Planning for sharing
Consent and ethics
Copyright
Documenting your data
Formatting your data
Storing your data
Strategies for centres
