Data-Management Plan (DMP) is a formal document describing how you plan to handle research project data during the research and after the research is completed. It describes what tools & techniques you will use to collect, store, manage and analyze this data. Mechanism to preserve research data and means to share it with others also form a part of DMP. Most agencies, which fund the research projects, require a DMP with every funding request.
A researcher normally takes care of all the above aspects of data management but documenting it helps in many ways. Writing down a plan will make it more formal, allow it to be shared & reviewed by peers. It will also help a researcher identify weaknesses and improve upon it. Research is a process of discovery and often requires changing tracks as your research progresses. DMP is a living document, and it must reflect these changes. Every change in DMP should be version controlled.
DMP consists of following aspects of Data Management
Data Collection –This part of DMP should cover the type of data collected, their format, collection methods, nature of data (stable or changing) and any external references.
Data Processing and Transformation –This part should cover how data is captured, managed and used for your project from initial capture to final delivery and analysis.
Data Formats and processing Tools–specify what file formats will be used for data collection and processing. Make use of commonly used data formats. If special data formats are used, how to read them should be specified.
Privacy, Confidentiality, and security of data- Aspects of privacy of sensitive data should be covered. Steps to minimize leakage should be highlighted. Strategies to protect confidential data should be specified.
Access rights and usage restrictions – it is accepted practice to share the final research data. A well-drafted license agreement will help with this case. If data is not shared, it should be backed up by a strong argument.
Metadata and Data Standards – metadata is “data about data." Community metadata standards help others in interpreting and using your research data. It is a good idea to specify the metadata standard you are using.
Data Documentation–A good documentation for your research data will facilitate its use by others. DMP should indicate the type of documentation you would provide with the data.
Data Storage during project stage- This section should specify how and where you will be storing the project data. It should specify the hardware platform and database software is used for storage.
Backup and Version control–research data should be backed up from time to time to mitigate the risk of accidental corruption or deletion. The backup plan and version control mechanism should be specified under this section.
Long-Term Storage and Preservation– this part should specify where you intend to store your working files and final research data. The details for both, the hardcopy and digital format should be specified.
There are several benefits of Data-Management Plan, and they are –
- Data can be located quickly whenever you need it.
- Multiple people can work simultaneously on the research. Continuity is maintained when one researcher leaves and another join the research.
- It prevents unwarranted rewriting, duplication or collection of data.
- It maintains a record of underlying publications making it easier to validate data.
- Research data can be shared easily for collaboration and further research.
- Your research has more impact and visibility.
- Research data can be used by other researchers, and you get credit for it.