methodology

Data Citation

Data citation is a practice of formally referencing datasets in research and publications to give credit to data creators, enable reproducibility, and facilitate data discovery. It involves assigning persistent identifiers (like DOIs) to datasets and including standardized citations in scholarly works. This methodology ensures data is treated as a first-class research output, similar to journal articles.

Also known as: Dataset citation, Data attribution, Data referencing, Persistent identifier citation, FAIR data citation
🧊Why learn Data Citation?

Developers should learn data citation when building or working with research data management systems, digital repositories, or scholarly publishing platforms to support open science and FAIR (Findable, Accessible, Interoperable, Reusable) data principles. It is crucial in fields like academia, government, and industry where data sharing and attribution are required for compliance, funding, or collaborative projects.

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