Research Data Management
This section outlines the guiding principles for the efficient data management in ANRF-funded
projects and associated matters.
What is Research Data Management?
Research Data Management (RDM) is a systematic and scientific process for managing data
throughout a research project, including its generation, documentation, processing, storage,
publishing, archiving, sharing, and access. RDM ensures adequate data governance in research
projects by ensuring ethical and legal compliance while working with private, personal or
sensitive data, along with addressing prevailing issues like data privacy, security, integrity,
quality and accessibility. Further, RDM helps to comply with the FAIR (Findable, Accessible,
Interoperable, and Reusable) data principles and seeks to promote the optimum reusability of
data by scientific community as well as the general public.
Why manage Research Data?
- To ensure:
- Are we FAIR? (referring to FAIR data principles)
- Findability, Accessibility, Interoperability, and Reusability of data
- Do we CARE? (referring to CARE principles)
- Collective Benefit, Authority to Control, Responsibility, and Ethics related to
data
- It will benefit us and our collaborators:
- Establishing how we will collect, document, organize, manage, and preserve our data at
the beginning of your research project has many benefits-
- Saves time and energy on data management
- Enables more focus on the research
- Easy for us and our collaborators to understand, find, use, and analyze
- It will benefit the scientific community
- Ideally, data should be managed so that any scientist (including the collector or data
originator) can discover, use and interpret the data after a period of time has passed.
How to manage Research Data?
By adhering to ANRF guidelines on Research Data Management, that mandates the preparation and
submission of a Data Management Plan (DMP) for all its project grants.
What is a Data Management Plan (DMP)?
A Data Management Plan (DMP) is a systematic document that details/records all the pertinent
information needed for robust data management, from data creation to its reuse, covering all
stages of the data lifecycle that comprises data collection, preparation, organization, processing,
analysis, storage, archiving, publication, sharing, and repurposing. It consists of various
questions related to various themes of data management processes that a data manager or the PI
needs to answer while conceptualizing a project proposal. Simply, a DMP is a brief plan to
define:
- how data will be created
- how it will be documented
- where it will be stored, transferred, backed up during the project or after the project
- how will it be shared & preserved
- how access will be granted to data wherever appropriate
- how data will be archived at the end of the project
- description of any ethical or legal compliances related to data
- provisions for the re-use of data
How to create a DMP?
Follow the link to register yourself on our ind-DMPTool ind-DMPTool is an interactive editor based
tool that facilitates easy and seamless creation of DMPs using pre-defined DMP templates and
guidance.