Reusing

What is data reuse?

Data reuse means using data for other purposes than it was originally collected for. Reuse of data is particularly important in science, as it allows different researchers to analyse and publish findings based on the same data independently of one another. Reusability is one key component of the FAIR principles.

Data that is well-described, curated and shared under clear terms and conditions is more likely to be reused. Integration with other data sources is also important, since that can enable new, yet unanticipated, uses for the data.
ELIXIR. “RDMkit – Reusing“.

For details, see RDMkit – Reusing

Researcher tasks anticipated during the reuse phase (external link)

Data analysis

Existing data

Licensing

Data quality

Data transfer

Identifiers

Data provenance

Reference information for the reuse phase

Examples of data citations

The case that data citation method has been specified：http://doi.org/10.32130/idr.3.1
Examples of data citations in a paper：https://www.nature.com/articles/s41597-023-02815-7#ref-CR19