When you submit a paper to a journal, do you check the journal’s research data policy? It is important to know what you may be asked to do about your research data in the publication process. Recently I attended a very informative webinar by Dr. Rebecca Grant; she explained data policies at SpringerNature, a major journal publisher. This post summarizes some important points that HKUST authors should know.
Publishers have been using policies to facilitate research data sharing. While major publishers formulate their own policies, there is a drive for them to work together for more consistent approaches.
Authors should note that these policies relate to data underpinning the articles being published, the portion that the conclusions rely on. Journals are often not interested in the wider datasets. These policies can differ depending on the discipline, the journal and the editorial team. It is therefore important that you check the policy of the journal you choose to submit your work.
Dr. Grant described the research data policies at SpringerNature: there are 4 types across their journals, some journals require Data Availability Statement (DAS), and a small number mandate data sharing.
4 Policy Types at SpringerNature
SpringerNature standardized the data policy into 4 types. The level of requirements goes up from Type 1 to Type 4.
- Type 1: data sharing and citation encouraged
- Type 2: data sharing and data availability statement encouraged
- Type 3: data sharing encouraged, data availability statement required
- Type 4: data sharing and citation required, data peer review
How can you comply with journal data policies?
- For Type 1 and 2, you can add a DAS if you like, and you can choose any data sharing options
- For Type 3, you have to write a DAS, and you can share data in the ways you like
- For Type 4, you must write a DAS and share your data in a repository
Data Availability Statement (DAS)
DAS is a short section in the manuscript that describes where other researchers can find the supporting data of an article. Here are two DAS examples:
“The data generated during the current study are available from the corresponding author on reasonable request.”
“All data generated and analyzed in this study are included in the published article as supplementary tables.”
DAS do not necessarily follow any templates, but you can find some suggested ones in this SpringerNature webpage.
Common Ways of Sharing
Authors can share data in different ways. Common ones include:
- on request
- supplementary materials in a published work
- author’s personal or project website
- data repositories
Among these, using data repositories is the most recommended option. If other researchers have to request data from authors, over time the contacts can be lost; or the authors themselves cannot access the data anymore due to various reasons. For data stored in project or personal websites, there is no guarantee that the links and even the sites are properly maintained in the long term. As for data shared via supplementary table, there may be an issue of re-usability; typical examples are data tables in Word document or PDF formats.
In contrast, data repositories are managed by organizations with a long-term commitment to providing access. They often provide your datasets with rich and standard metadata, landing page, Persistent ID, preservation service and guidance on how to cite. For example, HKUST researchers can use the data repository DataSpace@HKUST. Some research communities have specific subject repositories, such as GenBank. Find out more about data repositories in our library guide.
The collective effort to make research more accessible and reproducible is a worldwide trend. Making research data available is going to a norm. We would expect that more and more journals will set up policies on data peer review and data sharing.
— By Gabi Wong, Library
last modified December 29, 2020