Building a global infrastructure for research data
Elsevier endorses the Joint Declaration of Data Citation Principles, working to ensure widespread adoption
By Hylke Koers, PhD Posted on 4 June 2014
For data to be discovered and acknowledged, however, it must be widely accessible and cited in a consistent and clear manner in the scientific literature. This need has motivated Elsevier to take various actions over the years. In 2007, Elsevier signed the Brussels Declaration, which supports making raw research data freely available. And for many years, Elsevier has been collaborating with data repositories to set up bi-directional links between articles and data sets to help make data better discoverable and more usable.
Now, Elsevier has become one of the first publishers to endorse the Joint Declaration of Data Citation Principles, the culmination of a collaboration of stakeholders to lay out a set of common principles for data citations. These standards will help to make research data become an integral part of the scholarly record, properly preserved and easily accessible, while ensuring that researchers get proper credit for their work.
Joint Declaration of Data Citation Principles
- Importance: Data should be considered legitimate, citable products of research. Data citations should be accorded the same importance in the scholarly record as citations of other research objects, such as publications.
- Credit and Attribution: Data citations should facilitate giving scholarly credit and normative and legal attribution to all contributors to the data, recognizing that a single style or mechanism of attribution may not be applicable to all data.
- Evidence: In scholarly literature, whenever and wherever a claim relies upon data, the corresponding data should be cited.
- Unique Identification: A data citation should include a persistent method for identification that is machine actionable, globally unique, and widely used by a community.
- Access: Data citations should facilitate access to the data themselves and to such associated metadata, documentation, code, and other materials, as are necessary for both humans and machines to make informed use of the referenced data.
- Persistence: Unique identifiers, and metadata describing the data, and its disposition, should persist – even beyond the lifespan of the data they describe.
- Specificity and Verifiability: Data citations should facilitate identification of, access to, and verification of the specific data that support a claim. Citations or citation metadata should include information about provenance and fixity sufficient to facilitate verifying that the specific timeslice, version and/or granular portion of data retrieved subsequently is the same as was originally cited.
- Interoperability and flexibility: Data citation methods should be sufficiently flexible to accommodate the variant practices among communities, but should not differ so much that they compromise interoperability of data citation practices across communities.
You can endorse these principles by visiting the FORCE 11 website.
Of course, the journey does not end with the publication of the Joint Declaration. There's still a lot of work ahead to realize widespread adoption of these principles across the industry, and to translate them into concrete solutions. That includes technical work to ensure interoperability among platforms, but there's also the social aspect of encouraging researchers to cite data properly by raising awareness and explaining the benefits of formal data citations.
Elsevier remains involved in developing technical solutions and creating guidelines to implement the citation principles, both within Elsevier and beyond. In fact, several Elsevier journals have already published articles with proper data citations (see example below), and we strive to accelerate this and work towards a future where proper citation of research data will be a considered a common and valued practice.[divider]
How data citation works
The following reference is from the article "A new approach to predicting environmental transfer of radionuclides to wildlife: A demonstration for freshwater fish and caesium," published in Science of the Total Environment in 2013. The first reference uses a proper data citation, including the key bibliographical information for the data set and using a data DOI as unique, persistent identifier. The reference is included in the standard References list, and treated on equal footing with article citations. That also means readers will enjoy the same benefits as for article citations, including one-click deep links to the referenced material and the ability to quickly jump to the point in the article where this work was first cited.
How does Elsevier help researchers share their data?
We recognize that data is becoming larger, more versatile and more ubiquitous than ever, and this has brought new challenges for researchers when dealing with data. At Elsevier, we support researchers in making their data freely available, and we are continually working on ways to meet their data-related needs – be it the storage of data, sharing of data, publication of data-intensive research, connecting their publications to their data, or in discovering relevant data from others. In addition, we are contributing our expertise to building the infrastructure that is needed for the future.
This commitment takes many forms. For example, as part of Elsevier's Article of the Future initiative, we have developed in-article data tools such as 3D viewers integrated into the article, Executable Papers , and many other domain-specific tools that allow researchers to interactively explore and engage with data. In the same context, we collaborate with data repositories to enable bi-directional linking between articles and data (see also this list of data repositories we link with) and even pull in data from external data repositories and display it in interactive visualization tools integrated into the article. We are also launching new, data-centric journals in areas where there is a need for it, such the "Data in Brief" articles in Genomics Data.
Furthermore, we have updated our text & data-mining policy to make it easier for researchers to use articles published with Elsevier as a corpus of data for their research. And, finally, we are actively participating in global interest and working groups that are shaping the future of data and scholarly publication, such as Force11, the Research Data Alliance, and the Data Citation Synthesis Working Group that has delivered these Data Citation Principles.
Elsevier will continue to collaborate with the research community to develop new ways to enhance the way research data is stored, shared and discovered. This way, we can support reproducibility and reuse of research data across a diverse range of platforms to benefit the researcher and ultimately science as a whole.
Elsevier Connect Contributor
Dr. Hylke Koers is the Head of Content Innovation at Elsevier, leading a team that is responsible for enhancing the online article format to better capture and present modern-day research. Part of Elsevier's Article of the Future program, this includes improved online presentation, better support and visualization of digital content, and contextualization of the article by linking with data repositories and other sources of trusted scientific content on the web.
Before joining Elsevier in 2010, Hylke received a PhD in theoretical astrophysics from the University of Amsterdam and served as a postdoctoral research associate at the Université Libre de Bruxelles. He is based in Amsterdam.
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