When it comes to citations, we normally think about publications. Yet citing data is becoming more common – and why shouldn’t it be? Citing data comes with a range of advantages :
- Evidence shows that, if a publication cites data, it will be cited more
- Citing data acknowledges researchers’ efforts
- Linking publications to their underlying data allows transparency and reproducibility in research
- Links to data deposited online can be included in CVs and online profiles (e.g. ORCID )
- Deposited data contributes to impact evaluation instead of gathering dust in researchers’ desk drawers.
Equipment can be cited , too. This makes research more easily replicable, as a specific tool in an organisation can be referenced (e.g. via a permalink) and reused by other investigators.
Enabling data citation through research data management
Citing data is possible only when the authors deposit it in a repository and include metadata. You need their names, the publication date, a title and a DOI for a basic citation. However, there are other metadata fields that it is sometimes helpful to include, such as the data version and the resource type. Just like citing literature, you can choose between different citation styles, such as APA, Chicago, MLA and Oxford. The Digital Curation Centre collected some overarching guidance that works in most cases.
If you wish your data to be cited, we also recommend the following:
- Deposit the data in a trustworthy repository
- Use permissive licences
- Always cite your data sources
The role of metrics in research
Research data metrics (or indicators) can help you demonstrate the impact of your data sharing efforts and drive reward mechanisms. Clarivate Analytics maintains a data citation index , while altmetrics are a less formal approach to analysing the way data is perceived. Altmetrics include, e.g. the number of views or downloads, social media interactions, or recommendations. Altmetrics are starting to appear in several websites, such as figshare and SpringerNature’s Scientific Data. There is a wealth of other services that allow you to measure the impact of data and its citation based on metrics. However, they are all at a relatively early stage of development and there is no agreement upon the measures used to estimate real impact.
You should be mindful that some metrics might just be a measure of the level of attention received by data. Traditional citation counts are the most highly regarded, yet uncertainty plagues the field. We recommend that you cite data as often as appropriate, to push debate forward and drive attention on these pressing matters.