Research Data Management

A data management Plan (DMP) is a formal document that describes the data you expect to acquire or generate during the course of a research project, how you will manage, describe, analyze, and store those data, and what mechanisms (including digital data storage) you will use at the end of your project to share and preserve your data.
Research data sharing that underlies the findings reported in a journal article/ conference paper/thesis as set out in the NRF Open Access Statement. The findings reported in a journal article or conference paper should be deposited in accordance with the NRF Open Access Statement. It is acknowledged that some data generated are more sensitive than others. Before initiating the research, it is the grant holders’ responsibility to consider the following: confidentiality, ethics, security and copyright. Possible data sharing challenges should be considered in the DMP with solutions to optimise data sharing.
Researchers should note that publicly funded research data should be in the public domain, with free and open access, by default. Collaborators and co-investigators in the research project should be informed by the applicant that due to public funding and funder mandate, one is expected to share research data as openly as possible. The Data Management Plan should indicate which data will be shared. If (some) research data is to be restricted, an appropriate statement in the DMP and subsequent publication should explain why access to data is restricted.
The National Research Foundation has adopted and is given permission to use the DCC Checkist for Data Management Plan, and this can be used as a guide for developing the DMP. (http://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Checklist_2013.pdf)

What do I include in a DMP?

Information contained in a data management plan describes your plan for addressing many aspects of working with data. A DMP need not be lengthy, but it will typically address many relevant aspects of your data, including but not limited to:

Types of data - What is the source of your data? In what formats are your data? Will your data be fixed or will it change over time? How much data will your project produce?

Contextual details (metadata) - How will you document and describe your data?

Storage, backup and security - How and where will you store and secure your data?

Provisions for protection/privacy - What privacy and confidentiality issues must you address?

Policies for re-use - How may other researchers use your data?

Access and sharing - How will you provide access to your data by other researchers? How will others discover your data?

Archiving and providing access - What are your plans for preserving the data and providing long-term access?

Alternatively, you can use the questions below and any specific data management requirements from your funding agency to write your data management plan. 

1.  Project, experiment, and data description
   • What’s the purpose of the research?
   • What is the data? How and in what format will the data be collected? Is it numerical data, image data, text sequences, or modeling data?
   • How much data will be generated for this research?
   • How long will the data be collected and how often will it change?
   • Are you using data that someone else produced? If so, where is it from?
   • Who is responsible for managing the data? Who will ensure that the data management plan is carried out?
2. Documentation, organization, and storage
   • What documentation will you be creating in order to make the data understandable by other researchers?
   • Are you using metadata that is standard to your field? How will the metadata be managed and stored?
   • What file formats will be used? Do these formats conform to an open standard and/or are they proprietary?
   • Are you using a file format that is standard to your field? If not, how will you document the alternative you are using?
   • What directory and file naming convention will be used?
   • What are your local storage and backup procedures? Will this data require secure storage?
   • What tools or software are required to read or view the data?
3. Access, sharing, and re-use
   • Who has the right to manage this data? Is it the responsibility of the PI, student, lab, MIT, or funding agency?
   • What data will be shared, when, and how?
   • Does sharing the data raise privacy, ethical, or confidentiality concerns? Do you have a plan to protect or anonymize data, if needed?
   • Who holds intellectual property rights for the data and other information created by the project? Will any copyrighted or licensed material be used? Do you have permission to use/disseminate this material?
   • Are there any patent- or technology-licensing-related restrictions on data sharing associated with this grant?
   • Will this research be published in a journal that requires the underlying data to accompany articles?
   • Will there be any embargoes on the data?
   • Will you permit re-use, redistribution, or the creation of new tools, services, data sets, or products (derivatives)? Will commercial use be allowed?
4. Archiving
   • How will you be archiving the data? Will you be storing it in an archive or repository for long-term access? If not, how will you preserve access to the data?
   • Is a discipline-specific repository available? If not, you could consider depositing your data into the CWU ScholarWorks to store your data.
   • How will you prepare data for preservation or data sharing? Will the data need to be anonymized or converted to more stable file formats?
   • Are software or tools needed to use the data? Will these be archived?
   • How long should the data be retained? 3-5 years, 10 years, or forever?