What do you need to do? How do you gain maximum benefit from publishing your data?
- Drivers and Benefits of data citation and DOIs
- Getting started with data citation
- Access your local data management services to find out how you can publish your data, assign a DOI to it and cite it in your papers, reports and CV.
- Consider creating a data management plan to capture specific requirements around ownership, access to data and data licensing; as well as data citation details such as contributors that should acknowledged.
Not all data you create or use will be cited by you or others. For example, some working data or highly sensitive data will never form part of the scholarly record and become citable. This is similar to other types of research outputs - you wouldn't expect to cite the first draft of a journal article or a highly confidential client report.
Citable data is data you expect will be persistently stored and managed for the appropriate period for a scholarly record. It should be described with a minimum set of metadata to enable accurate citation. Best practice is for citable data to be assigned a persistent identifier, preferably a DOI, that can be included in the data citation to facilitate access to the data.
In a nutshell, in order to cite your data, you first need to publish the data, or at very least, a description of the data. You should talk to your institution about the best way to do this, but in general terms this will involve:
- confirming you are able to publish the data by considering issues such as contractual arrangements, copyright and ethics
- determining the licence conditions under which the data can be released and reused
- preparing the data for publication by considering issues such as data cleansing and file formats
- securely storing the data to enable ongoing management and access
- assigning a DOI to the data
- providing appropriate metadata to describe the data including citation information
- publishing the metadata including the DOI.
A number of these steps may already have been undertaken during data management planning.
Once you have published your data, you can cite it in your publications and professional profile including your CV and publications lists.
Data citation can be used to attribute data you've used and to promote your research output in similar ways to publications.
- Follow recommended data citation formats - APA (6th ed), MLA (7th ed), Chicago (18th ed), etc. - examples.
- Link your data to your publications and vice versa, by:
- linking data to publications, derived datasets and associated software - see example
- citing your data in your reference list
- citing data in supplemental material
- Formally reference other datasets you have used in your publications - see example.
- Take advantage of new forms of publications such as data journals - see example.
- As part of your researcher profile
Formal publication and citation of data supports the recognition of research data as a first class research output. It also enables the generation of citation metrics for research data outputs.
Thomson Reuters Data Citation Index
Other less formal measures may also apply to published data. These include a range of altmetrics such as number of views, number of downloads, social media "likes" and recommendations. Such metrics are becoming increasingly common across a range of data publishing models including data repositories and data journals. Because of their immediacy, altmetrics can be an early indicator of the impact or reach of a dataset, before the long tail of formal citation metrics can be assessed. Digital Science's Altmetric service aggregates online attention for research outputs, such as mainstream and social media, online reference managers, Wikipedia, blogs, F1000 and public policy documents. Scientific Data is one data journal that displays Altmetric scores for data.
Some of the benefits to researchers of providing Altmetrics on a CV are to:
- uncover the impact of just-published work
- legitimise all types of scholarly products
- recognise diverse impact flavours
- encourage a focus on public engagement
- spur innovation in research evaluation.
Data citation offers an extension to current measures of research impact. Accurately citing data brings benefits to researchers which include:
- raising your researcher profile
- adding citable references to data outputs on biosketches and in CVs
- an additional metric to complement your traditional publications metrics
- evidencing that citing data is associated with increased citation rates
- fulfilling funder requirements which stipulate publishing research outputs
- tracking the reach, impact and reuse of all your research outputs
- taking advantage of emerging opportunities to quantify data impact through:
ANDS poster on encouraging Data Citation