10 Sports Science Data Things: Thing 6

Thing 6: Data citation for access and attribution

Citation analysis and citation metrics are important to the academic community. Find out where data fits in the citation picture.

What does a data citation look like?

A dataset citation includes all of the same components as any other citation:

  • author,
  • title,
  • year of publication,
  • publisher (for data this is often the archive where it is housed),
  • edition or version, and
  • access information (a URL or other persistent identifier).


Nemenman, Ilya (2015): Data and plotting scripts file for the project. Figsharehttps://doi.org/10.6084/m9.figshare.1491421.v1 Retrieved 23:05, Jul 22, 2015


Getting more out of your citation

Data citation continues the tradition of acknowledging other people’s work and ideas. Along with books, journals and other scholarly works, it is now possible to formally cite research datasets and even the software that was used to create or analyse the data.

  1. Have a look at this dataset from the Australian Longitudinal Study of Aging. Data Citations are available from the Thomson Reuters Data Citation Index - note the number of times this dataset has been cited

  2. Scan through the ANDS introduction to data citation
  3. Now look at the Hutchinson Drought Index data record in Research Data Australia.
    1. This research data makes cross disciplinary connections between episodes of drought and correlated increases in rural mental health issues.
    2. The beauty of this record is that it shows the entirety of the research outputs - publications, software, related datasets and more - all of which are citable.
    3. Click on the ‘Cite’ button to see the similarities between the formats for citation of data and other scholarly publications.  Did you notice that, as yet, there are no citation metrics to this record?

Consider: Data citation is a relatively new concept in the scholarly landscape and as yet, is not routinely done by researchers, or expected by most journals. What could be done to encourage routine citation of research data and software associated with research outputs?

Citing data and DOIs

DOI (Digital Object Identifiers)

A DOI Name (DOI) is a specific type of Handle and can be assigned to any object that is a form of intellectual property. DOI should be interpreted as ‘digital identifier of an object' rather than ‘identifier of a digital object'.

Consists of a unique, case-insensitive, alphanumeric character sequence that is divided into two parts, a prefix and a suffix, separated by a forward slash.

Example: 10.1594/PANGAEA.484677

Whilst Digital Object Identifiers (DOIs) are not essential for data citation, they are a very useful tool to not only track data citation metrics but to also link DOIs from journal articles and other related services (e.g. software associated with the dataset).

Contact the Library about how to gain a DOI for your dataset through the ANDS Cite My Data service - http://ands.org.au/services/cite-my-data.html


Persistent identifiers and data citation explained

Data citation principles

The Force11 Joint Declaration of Data Citation Principles are based on the premise that data citation, like the citation of other evidence and sources, is good research practice and is part of the scholarly ecosystem supporting data reuse.

Since they were published in 2014, the Principles have been endorsed by numerous individuals and more than 100 data centres, publishers and societies.

1. Start by reading the Force 11 Principles:

2. Then browse the list of people and organisations that have endorsed the Principles:

Consider: Given such support and clear direction, why do you think data citation has not been uniformly adopted, so far, across all disciplines?