Thing 7: Data citation for access & attribution

Overview

Teaching: 0 min
Exercises: 0 min

Questions

• How does data fit in the citation analysis and citation metrics pictures?

Objectives

• 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 analyze the data.

Explore Data Citation Usage

1. Let’s look at the Weddell Seal data in ANDS. Check out how many times it has been cited. This citation count has been measured by Thomson Reuters Data Citation Index product.
2. Scan through the ANDS introduction to data citation
3. 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.
   • 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? 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 some 2 years ago, the Principles have been endorsed by numerous individuals and more than 100 data centers, publishers and societies.

Evaluate the Force11 Principles

1. Start by reading the Force11 Principles
2. Then browse the list of people and organizations that have endorsed the Principles.
3. 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?

Data Visualization Tools

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 infogr.am tutorial to create a data visualization using your own data or the titanic passenger dataset they have provided.

Consider the Tool You Used

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 visualization is likely to make the data more or less accessible, reusable and therefore citable.

Key Points

• First key point.