To build a more open, transparent, and reliable research landscape, LIDSEN encourages authors to share research data underlying the results of their articles so as to promote the discoverability of the work, the reproducibility of results, the reusability of data, and collaborations among researchers.
"Research Data" refers to the underlying data collected, observed, or created by researchers in the course of their work for the purpose of analysis to produce the research results. What research data look like varies by discipline and subject area, such as print, digital, or physical form. Authors should provide at least the minimum data required to reproduce the results presented in the article. Examples include (but are not limited to): software, code, algorithms, protocols, methods, materials, photographs, videos, gene sequences, interview transcripts, etc.
Before making a decision regarding sharing data, authors should check if the data is appropriate for being shared. You may consult your institution or research funder for any relevant requirements. The SHERPA/JULIET, which tracks funders’ policies on data archiving, may help you identify the policy your funder follows. Where sharing the data may raise ethical, legal, or security issues, or where the data you’ve used in your research were licensed from a third party, then it should not be shared. According to the recommendations of the International Committee of Medical Journal Editors (ICMJE), patients have a right to privacy that should not be violated without informed consent, therefore confidential data, such as data involving human subjects, should always be anonymized or should be shared in accordance with the terms of the consent signed by the participants. Please be aware that data deposit ahead of submission will not be considered as a prior publication.
Data may be shared in either discipline-specific or generalist data repositories, which are online platforms where researchers can deposit datasets associated with their work.
Typically, data should be submitted to discipline-specific, community-recognized repositories whenever possible, especially those that support FAIR Data Principles or that at least issue a persistent identifier for your data. If no discipline-specific repositories are available, then it can be submitted to a generalist repository such as Dryad, Figshare, Zenodo, and more. You may be able to choose an appropriate data repository according to the following checklist.
1. Learn about the data sharing policy your target journal adheres to;
2. Check the requirements of your institution or funder. Some funders may have designated repositories for researchers to store their data;
3. Consult librarians or colleagues for advice. They may provide a recommendation on the repository that is relevant to your discipline;
4. Visit re3data.org and fairsharing.org for lists of registered and certified data repositories to search for a suitable repository, if the above three options are not available.
The repository may give you instructions on how to organize your data and information for deposition and ask you to select from a range of license choices to make your data available. Examples of data licenses that support open and free use of your data include Creative Commons licenses, such as CC0 (public domain) and CC-BY 4.0 (free usage with attribution).
A Data Availability Statement (DAS) provides a description of where the research data associated with a paper is available and how it can be accessed. The data can be primary data (data the authors generated as part of their study) or secondary data (data from other sources that the authors reused in their study). The statement will be placed under the heading "Data Availability Statement" before the reference list in the final published article, and it may include the following:
Confirmation of whether the data underlying the paper exists. If no datasets were generated or analyzed in your article, we encourage you to state this as well. If the data exists, this statement will describe how it can be accessed.
Statement of what the data is and where it can be found. If the data are in repositories, please include hyperlinks and persistent identifiers (e.g. DOI or accession number) for the data (where applicable).
Clarification of any conditions or restrictions for accessing or reusing the data. If accessing or reusing the data is subject to any conditions of use or restrictions (e.g. license, embargo, privacy or ethical restrictions, and more), these should also be described in the data availability statement.
The International Committee of Medical Journal Editors (ICMJE) provides further guidance on how to compose a rich statement and on the secondary analyses using shared data. Authors should also check if the funder has any specific requirements regarding the data availability statement.
The table below outlines the elements recommended to be included in a Data Availability Statement, however, please be aware that it may not apply to all specific cases.
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Availability of Data |
Data Availability Statement |
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Data are openly available in a public repository |
Please include the following in the statement:
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Data are available on reasonable request due to restrictions |
Please include the following in the statement:
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Data are subject to third party restrictions |
Please include the following in the statement:
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Data are available within the article and/or its supplementary materials |
Please state “[describe which data here if possible] are available within the article [and/or] its supplementary materials.”. |
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Data sharing is not applicable as no data are generated or analyzed |
Please state “Data sharing is not applicable to this article as no data were generated or analyzed in this study.”. |
If you refer to a data set in writing your article, you’ll need to cite it properly so as to ensure that individual contributions are credited. This applies whether it’s data you’ve collected yourself or generated by other researchers.
You are required to cite the data at the relevant place in the manuscript text and in addition include a formal citation in the reference list, just like the same way as article, book, and web citations. We recommend following the format proposed by the Joint Declaration of Data Citation Principles for citing the data:
Authors; Year; Dataset title; Data repository or archive; Version (if any); Persistent identifier (e.g. DOI)
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