Effective research data management is essential for reproducible, sustainable research, and open data. Chalmers Data Office provides support to ensure that research data is managed in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable), from data management planning to publication and long-term preservation.
FAIR
FAIR is an acronym for Findable, Accessible, Interoperable, and Reusable. The FAIR principles ensure that research data are easy to find, include information on how to access them, are compatible with other data, and can be reused. These principles play a key role in the advancement of open science and serve as fundamental guidelines for good data management and open access to research data.
Findable – How can data be found?
Data and metadata should have a unique and persistent identifier, be searchable via web services, and be described with rich, machine-readable metadata.
Accessible – How can data be accessed?
Data should be accessible through open and standardized protocols, with access control mechanisms if needed, and metadata should remain available even if the data is no longer accessible.
Interoperable – Are data and metadata interoperable?
Data and metadata should use standardized formats, vocabularies, and semantic descriptions to ensure they can be integrated and understood across different systems.
Reusable – Can others use the data in the future?
Data should have rich metadata, clear licensing terms, and documented provenance to enable meaningful reuse within and beyond its original context.
Read more about FAIR research data at SND.
