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The 10 marine science (rd) Things: Thing 7

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.

Activity 1: 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 Australia Longitudinal Study of Aging.

Data Citations are available from the Clarivate 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 Hutchison Drought Index data record in Research Data Australia.

a. Click on the link below to read an article describing how this data makes cross disciplinary connections between episodes of drought and correlated increase in rural mental health issues.

b. The beauty of the Hutchison record is that it shows the entirety of the research outputs - publications, software, related datasets and more - all of which are citable.

c.  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?

Activity 2: 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?

An Example of Data Re-Use

Original dataset:

Related publication re-using drought dataset in a novel way:

Note: When an original dataset is re-used by another author:
- the author of the original dataset can be included as a author or acknowledged in the new publication
- the original dataset (& it's DOI) is included in the reference list of the subsequent researcher's article

Persistent identifiers and data citation explained

Activity 3: DOIs are unique (just like you)

Digital Object Identifiers (DOIs) are unique identifiers that provide persistent access to published articles, datasets, software versions and a range of other research inputs and outputs. There are over 120 million Digital Object Identifiers (DOIs) in use, and last year DOIs were “resolved” (clicked on) over 5 billion times!

Each DOI is unique but a typical DOI looks like this: 10.4225/08/50F62E0D359D5

DOIs can be used to collect citation metrics about the use of a dataset or article.

1. Start by watching the following short 4.5min video explaining on persistent identifiers and data citation from Research Data Netherlands. It gives you a succinct, clear explanation of how DOIs underpin data citation.

2. Have a look at the poster "Building a culture of data citation". follow the arrows to see how DOIs are attached to data sets.

3. Let’s go to a data record which shows how DOIs are used. Click on this DOI to ‘resolve’ the DOI and take us to the record, "X-ray fluorescence and particle surface area data for surface seabed sediments in Jervis Bay, NSW (June and August 2008 and February 2009)”

The same record has been syndicated to Research Data Australia. 

Click on the DOI at the bottom of the page, under ‘Identifiers’. No matter where the DOI appears it always resolves back to its original dataset record to avoid duplication. i.e. many records, one copy.

Want to know more about DOIs? have a look at the ANDS DOI Guide page.

Consider: Should DOIs be routinely applied to all research outputs? Remember that DOIs carry an expectation of persistence (maintenance costs etc.) but can be used to collect metrics as well as link articles and data (evidence of impact).