Thing 7: Data citation for access & attribution
Citation analysis and citation metrics are important to the academic community. Find out where data fits in the citation picture.
- Getting started: how to cite data
- Learn more: may the FORCE(11) be with you (while you cite data)
- Challenge me: are some data formats more likely to be cited?
Getting started
Citing research data
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.
- Start by looking at the Weddell Seal dataset. Check out how many times it has been cited. This citation count has been measured by Thomson Reuters Data Citation Index product.
- Scan through the ARDC introduction to data citation
- Now look at the Hutchinson Drought Index data record in Research Data Australia. This research data makes cross disciplinary connections between episodes of drought and correlated increases in rural mental health issues. 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. Has this dataset been cited yet?
- Click on the ‘Cite’ button to see the similarities between the formats for citation of data and other scholarly publications.
If you have time, poke around Dryad repository to see how it has integrated citation of related articles and data.
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?
Learn more
Data citation principles
The Force11 Joint Declaration of Data Citation Principles are a set of principles for citing data. They 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, the Principles have been endorsed by numerous individuals and more than 100 data centres, publishers and societies.
- Start by reading the Force11 Principles
- 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?
Challenge me
Data formats and data citation
Are some data formats more likely to be cited?
It has become a lot simpler to mine data and interpret insights in an engaging, attractive and easy to understand way. Does this make the data more or less accessible, reusable and therefore citable?
1. Go to this list, from econsultancy.com, of various free and premium tools and platforms for creating interactive charts, infographics, maps and word clouds.
2. Choose one tool and delve into the detail.
3. If you want to get hands on, work through this infogram tutorial to create a data visualisation using your own data or the titanic passenger dataset they have provided.
Consider:
1. What are 3 of your likes or dislikes about the tool you explored?
2. What is your opinion about whether publishing data as a visualisation is likely to make the data more or less accessible, reusable and therefore citable?
Do you have a question? Want to share a resource?
- Post to the Data Librarians Slack group to connect with the community.
- Tweet to @ardc_au using hashtag #23things
Keep on going to the next thing: DOIs and citation metrics for data or return to all the things