Open Data and Accessible Source Materials Guidelines (HSS)
Open Data and Accessible Source Materials Guidelines (HSS)
- What are Open Data and Accessible Source Materials
- What is required when submitting an article
- Further Guidance on Open Data requirements for new datasets you have generated
- Further guidance on Open Data requirements for existing datasets you have reused
- Further Guidance on Accessible Source Materials
- Limited exceptions to these guidelines
- The FAIR Data Principles
- Gates Open Research-approved repositories
These guidelines relate to the Gates Open Research policy on data availability, which requires all authors to share the underlying data which relates to their article. The policy text can be read here.
If you cannot share your data, for example for ethical reasons, a limited number of exceptions to these guidelines are provided below.
For more information on each of the requirements, please see Further Guidance.
What are Open Data and Accessible Source Materials?
The data and sources underpinning your article may consist of archival documents, museum objects, audio files, AV material, images, transcripts, field notes, survey results, socioeconomic-, qualitative and quantitative datasets or other materials, which formed the input to, or output of your research. They may consist of physical objects, digitised materials or born digital files. Depending on your study design, you may have reused existing data or sources, or generated new datasets.
Gates Open Research requires you to provide access to all of the data and sources you have generated or reused in your research. This is a key step to ensure that your research and methods are transparent and that your results can be reproduced (where relevant).
- If you generated new datasets (for example field notes, survey responses, interview transcripts), you must deposit them into an appropriate data repository, and describe how they can be accessed and reused by others in your Data Availability Statement.
- If you reused existing datasets (for example Open Government datasets or data generated by another researcher) you must describe how they can be accessed and reused by others in your Data Availability Statement.
- If you used other source materials, for example from libraries, archives or museum collections, you must describe how they can be accessed and reused by others in your Data Availability Statement.
You should assume that if you have written a research article, there are data or source materials associated with your study, and you should therefore provide readers of your article with enough information to allow them to be accessed and potentially reused.
The Heritage Data Reuse Charter may assist humanities researchers in considering how data sharing applies to their research practice and the reuse of data from cultural heritage institutions.
1. What is required when submitting an article
- Your dataset(s) must be deposited in an appropriate data repository.
- Your dataset(s) must have a license applied which allows reuse by others (CC0 or CC-BY).
- Your dataset(s) must have a persistent identifier (e.g. a DOI, ARK or Handle), allocated by a data repository.
- You must provide a data availability statement as a section at the end of your article, including elements 1-3.
- You must include a citation for each dataset and add it to your reference list.
- Your dataset(s) should not contain any sensitive information, for example in relation to human research participants.
- You should share any related software and code.
- Your dataset(s) must be useful and reusable by others, adhere to any relevant data sharing standards in your discipline and align with the FAIR Data Principles.
- Your dataset(s) should link back to your article, if possible.
- You must provide a data availability statement as a section within your article, describing where the dataset is located and how it can be accessed by others.
- You must include a citation for each dataset and add it to your reference list.
- You must provide a data availability statement as a section within your article, describing where the source material is located and how it can be accessed by others.
- You must include a citation for your source and add it to your reference list.
If you fail to adhere to these guidelines when submitting, the publication of your article may be delayed, and your article may ultimately be rejected.
2. Further Guidance on Open Data requirements for new datasets you have generated
2.1 Your dataset(s) must be deposited in an appropriate data repository
Before submission, you should deposit your data in an appropriate data repository and ensure that the dataset is published openly on the web. For dynamic datasets which continue to evolve or change over time, please deposit a snapshot of the data reflecting its state at the time when you produced the analysis you are publishing.
The repository you choose must supply you with a persistent identifier (for example a DOI, ARK, Handle or URN) and allow you to apply an open license, which must be CC0, CC-BY 4.0 or equivalent. Please include descriptive legends and, where applicable, coding schemas alongside your datasets.
Most repositories do not charge a fee for deposit; however, a fee may apply if the repository provides data checking or curation services; or if you are storing very large datasets (for example over 100GB).
Discipline-specific repositories
Gates Open Research strongly encourages the use of community-recognised and discipline-specific repositories where they are available, for example those provided specifically for quantitative or qualitative social sciences datasets.
Controlled access repositories
If you cannot share your data openly, for example to protect the privacy of your research participants, you may choose to use a repository which restricts or controls who can access your data and for what purposes.
Generalist repositories
If there is no appropriate discipline-specific repository available, please deposit your data at a generalist data repository, an institutional data repository (for example provided by your university), or a national data repository. A list of generalist data repositories is available below.
2.2 Your dataset(s) must be openly licensed
To allow the maximum possible reuse, your dataset(s) should be published with a CC0 Public Domain Dedication, which does not retain any rights to the data. Alternatively, a CC-BY 4.0 Creative Commons Attribution Only license, which requires others to attribute you when using the data, is acceptable. Your chosen repository should allow you to apply a CC0 Public Domain Dedication, CC-BY 4.0 license or equivalent to your data.
Copyright limitations: Some studies involve the collation, or even digitisation, of materials for which the author does not own copyright. If you do not own the copyright for your dataset or source materials, you must seek permission from the copyright owner before depositing the dataset into a repository and applying an open license. If you cannot share the data in a repository or under an open license for copyright reasons, this can be explained in your data availability statement.
For software and source code, we strongly advise you to use an OSI-approved license.
2.3 Your dataset(s) must have a persistent identifier
Persistent identifiers allow datasets to be uniquely identified on the web. Commonly used persistent identifiers include DOIs and accession numbers, but other persistent identifiers such as PURLs, ARKs, Handles or URNs are also acceptable. Your chosen data repository should provide you with a persistent identifier for each dataset that you deposit.
2.4 You must provide a data availability statement
You must include a data availability statement at the end of your article, before the references list, describing each dataset and including a link to the relevant repository and the dataset’s persistent identifier.
When drafting the statement, please include:
- The name of the repository used;
- A brief description of the contents of each dataset;
- A statement that the dataset has a CC0 Public Domain Dedication or CC-BY 4.0 license applied.
If your data must be restricted for legal, ethical, or other reasons, please see below for further information on what should be included in your data availability statement.
Examples:
| Data Type | Data Availability Statement Example | Data Citation Example |
| Data deposited into a generalist repository |
OSF: Home food growing, well-being and food security during the COVID-19 UK lockdown. https://doi.org/10.17605/OSF.IO/7EZJQ (Mead, 2021) This project contains the following underlying data: Home food growing lockdown study data Mead.sav pre-pandemic UA opinon comparison.sav Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). |
Mead B: Home food growing, well-being and food security during the COVID-19 UK lockdown. 2021. http://www.doi.org/10.17605/OSF.IO/7EZJQ
Example taken from: Mead BR, Davies JAC, Falagán N et al. Growing your own in times of crisis: the role of home food growing in perceived food insecurity and well-being during the early COVID-19 lockdown. Emerald Open Res 2021, 3:7 (https://doi.org/10.35241/emeraldopenres.14186.2) |
| Literature as a dataset |
OSF: Meter and Memory. DOI: 10.17605/OSF.IO/A825X (Andreetta et al., 2021). The project contains the following underlying data: all Ariosto.xlsx (Responses to the non-poems derived from the Orlando Furioso). all Dante.xlsx (Responses to the non-poems derived from the Divina Commedia). |
Andreetta S, Soldatkina O, Boboeva V, et al.: Meter and memory. OSF. 2021. http://www.doi.org/10.17605/OSF.IO/A825X Example taken from: Andreetta S Oleksandra S, Boboeva V and Treves, A. In poetry, if meter has to help memory, it takes its time. Open Research Europe 2021 (https://doi.org/10.12688/openreseurope.13663.2) |
| Data with access restrictions (see below for a list of acceptable reasons to restrict access) |
The interview data generated and analysed during the current study cannot be sufficiently de-identified and therefore cannot be made publicly available, due to ethical considerations. In addition, the raw bibliometric analyses data that supported the interview sampling cannot be made publicly available, due to Scopus’ and University of Cambridge’s licence agreements. The data could potentially be made available upon reasonable request, for the purpose of further research. For this, please contact the corresponding author. However, the following data is available. Apollo: Research data supporting [How academic sabbaticals are used and how they contribute to research – a small-scale study of the University of Cambridge], https://doi.org/10.17863/CAM.77152 (Wooding & Ioppolo, 2021) This project contains the following underlying data:
|
Wooding S, Ioppolo B: Research data supporting [How academic sabbaticals are used and how they contribute to research – a small-scale study of the University of Cambridge] [Dataset]. 2021. https://doi.org/10.17863/CAM.77152 Example taken from: Ioppolo B and Wooding S. How academic sabbaticals are used and how they contribute to research – a small-scale study of the University of Cambridge using interviews and analysis of administrative data. F1000Research 2022, 11:36 (https://doi.org/10.12688/f1000research.74211.2) |
| Data in a controlled access repository |
Irish Social Science Data Archive: Lived Lives, https://www.ucd.ie/issda/data/livedlives/ (Lived Lives, 2021). Study number (SN): 0070-00 This project contains the following underlying data: – Lived_Lives_Quantitative_Data_Paper2_SPUH (Excel file containing quantitative data collected at Lived Lives SPUH) – Lived_Lives_Conference_Room_Transcript_Paper2_SPUH (Word file containing anonymised transcription of post-exhibition interactive conversation with the Lived Lives team) – Lived_Lives_Paper2_SPUH_Qualitative_Feedback (Word file containing quantitative data collected at Lived Lives SPUH) – Lived_Lives_Walsh_and_Phillips_Feedback_and Evaluation (Word document containing evaluations of Lived Lives by Dr. Consilia Walsh and Dr Áine Phillips) These data are under restricted access due to the sensitivity of the subject material. To access the data, please complete a ISSDA Data Request Form for Research Purposes, sign it, and send it to ISSDA by email (issda@ucd.ie). Researchers will be asked to provide a description for the intended use of the data and will be asked to agree to the terms of use, as outlined in the request form. Data access will be granted for teaching and research purposes under ISSDA terms and conditions. |
Lived Lives: Lived Lives I: A Rural Perspective; Lived Lives II: A Psychiatric Hospital Perspective, 2020. [dataset]. Version 1. Irish Social Science Data Archive. 2021. Example taken from: Malone KM, Cleary E, Kelleher CC et al. Bringing Lived Lives to Swift’s Asylum: a psychiatric hospital perspective. Wellcome Open Res 2021, 6:85 (https://doi.org/10.12688/wellcomeopenres.15588.3) |
| Articles without data | No data is associated with this article. | Not applicable |
| Articles where the data consists of bibliographic references | The data for this article consists of bibliographic references, which are included in the References section. | Standard bibliographic references |
2.5 You must include a data citation and add a reference to data to your reference list
Your dataset should be cited in the body of your article, and you should add the dataset to your reference list as you would any other bibliographic citation.
You may use your preferred referencing style but should include, at a minimum:
Dataset creator; Publication year; Dataset title; Name of repository where the data is located; Persistent Identifier (e.g. DOI, ARK, URN etc.)
Please add [Data] to the reference to denote its type.
2.6 Your dataset(s) must not contain any sensitive information
It is your responsibility to share data ethically and, where relevant, protect the privacy of your research participants. You should ensure that your datasets have been de-identified in accordance with the Safe Harbor method before submission.
Data sensitivity is not only connected to human research participants, so please check your datasets for other sensitive elements, for example the locations of protected archaeological sites.
2.7 You should share any related software and code
All articles should include details of any software and code that is required to view the datasets described or to replicate the analysis.
For Software
For all software used, please state the version, details of where the software can be accessed, and any variable parameters that could impact the outcome of the results. If you have coded software in-house, the source code should be archived under an open license and shared. For code stored in GitHub, you should create a ‘public registration’ for your project to obtain a DOI.
Information about software should be included in a software availability statement, which you can add to the end of your article, before the references list.
When drafting the statement, please include:
- Software available from: URL for the website where software can be downloaded from, if applicable.
- Source code available from: URL for versioning control system (for example GitHub).
- Archived source code at time of publication: DOI and citation for project in Zenodo.
- License: Must be an open license and preferably an OSI-approved license.
If there are ethical or privacy considerations as to why the source code may not be made available, please contact the editorial team.
For analysis code
If you have created custom analysis code, this should be archived under an open license and shared. For analysis code stored in GitHub, you should create a ‘public registration’ for your project to obtain a DOI. We recommend using an OSI-approved license, but CC-BY 4.0 is also acceptable.
Information about your archived analysis code should be included in your data availability statement, which you can add to the end of your article, before the references list.
When drafting the statement, please include, under the heading “Extended Data”:
- Analysis code available from: URL for versioning control system (for example GitHub).
- Archived analysis code as at time of publication: DOI and citation, e.g. from Zenodo.
- License: Must be an open license and preferably an OSI-approved license or CC-BY 4.0.
Code and software should be cited in the body of your article, be added to your reference list as you would any other bibliographic citation.
You may use your preferred referencing style but should include, at a minimum:
Creator(s); Publication year; Title; Publication venue; Publication date; Persistent Identifier (e.g. DOI); Version.
Please add either [Software] or [Code] as part of the reference to denote its type.
2.8 Your dataset(s) must be useful and reusable by others, adhere to any relevant data sharing standards in your discipline and align with the FAIR Data Principles
The FAIR Data Principles: Gates Open Research endorses the FAIR Data Principles as a framework to promote the broadest reuse of research data. Datasets which are “FAIR” are Findable, Accessible, Interoperable and Reusable. More information on the FAIR Data Principles and how you can align your data sharing methods with them is available here.
You can read more about FAIR data sharing in the humanities here: Sustainable and FAIR Data Sharing in the Humanities.
Relevant data sharing standards: Data standards help you to align with common data sharing practices in your field, for example how your data should be structured, formatted and annotated. Please check FAIRSharing.org for details of data standards specific to the topic of your research.
2.9 Your dataset(s) should link back to your article
Some data repositories provide functionality which allows you to add links to any published articles associated with your dataset. If possible, we recommend that you update your metadata record in the data repository to include a link to your article. You can link to the article using your article DOI, which will be emailed to you when your article is published.
3. Further guidance on Open Data requirements for existing datasets you have reused
When you reuse an existing dataset, whether it is connected to previous research you have conducted, the findings of another researcher, or from other sources like Open Government data portals, it is important that you are transparent about the dataset’s location and how others can access it.
3.1 You must provide a data availability statement as a section within your article, describing where the dataset is located and how it can be accessed by others
You must include a data availability statement at the end of your article, before the references list, describing each dataset and including a link to the relevant repository and the dataset’s persistent identifier. For dynamic datasets which continue to evolve or change over time, please indicate how you accessed the subset of data you have analysed, and when the data was accessed.
When drafting the statement, please include:
- The name of the repository where the dataset can be found;
- A brief description of the contents of each dataset;
- A description of the license applied to the dataset, if available.
If the dataset has been restricted or you encountered particular access conditions when using it, please include this information in your data availability statement.
Examples:
| Data Type | Data Availability Statement Example | Data Citation Example |
| Census data |
Individual-level data from the 1940 US Census is available from IPUMS https://doi.org/10.18128/D010.V8.0.EXT1940USCB. These data are under Copyright of Minnesota Population Center, University of Minnesota. Access to the documentation is freely available without restriction; however, users must register before extracting data from the website. The output of the TopDown algorithm when run on the 1940 US Census data is available to download from the US Census Bureau: https://www2.census.gov/census_1940/. These data are under Copyright of the United States Census Bureau. |
Ruggles S, Flood S, Goeken R, et al.: IPUMS USA: Version 8.0 extract of 1940 Census for U.S. Census Bureau disclosure avoidance research [dataset]. 2018. http://www.doi.org/10.18128/D010.V8.0.EXT1940USCB Example taken from: Petti S and Flaxman AD. Differential privacy in the 2020 US census: what will it do? Quantifying the accuracy/privacy tradeoff. Gates Open Res 2020, 3:1722 (https://doi.org/10.12688/gatesopenres.13089.2) |
| Third-party survey data |
DCMS Survey. One dataset used in this paper is composed of responses to DCMS survey release for quarter 4 of their longitudinal survey titled ‘Taking Part’ (see DCMS (2017a), available at: https://www.gov.uk/government/statistics/taking-part-201617-quarter-4-statistical-release (accessed 30-Jan-2020) under the Open Government License agreement. BFI survey. One dataset used in this paper is composed of responses to a British Film Institute (BFI) survey titled: ‘Cultural Consumption’ conducted by IpsosMORI in 2011. The BFI provide the survey dataset as appendix 4 of their larger report: Northern Alliance and Ipsos MediaCT (2011) Opening our eyes: How film contributes to the culture of the UK (Report), London: British Film Institute. Available at: https://www.bfi.org.uk/about-bfi/policy-strategy/opening-our-eyes-how-film-contributes-culture-uk |
DCMS: Taking Part Survey: England Adult Report, 2016/17 – Statistical release quarter 4’ [dataset]. DCMS/Crown: London. 2017a; (accessed 30-Jan-2020). https://www.gov.uk/government/statistics/taking-part-201617-quarter-4-statistical-release. Example taken from: Hanchard M, Merrington P, Wessels B et al. Developing a computational ontology to understand the relational aspects of audience formation. Emerald Open Res 2020, 2:5 (https://doi.org/10.35241/emeraldopenres.13465.1) |
| Third-party data in a controlled access repository |
The linked dataset was analysed within the NHS National Safe Haven, provided by NHS Research Scotland. The Safe Haven is a remote server through which the researcher accesses the health data and services to enable research while protecting the confidentiality of the data. Data remains under the control of the NHS and complies with legislative and NHS policies. The linked dataset is archived within the Safe Haven and is available by application to NHS Scotland via the electronic Data Research and Innovation Service (eDRIS), within NHS National Services Scotland (https://www.isdscotland.org/Products-and-Services/eDRIS/). To apply for access to these data, please read the guide for researchers and then complete the Enquiry Form, describing your planned study and the data required, and email it to nss.edris@nhs.net. |
NHS NSS Information Services Division: SMR Datasets. 2017. http://www.ndc.scot.nhs.uk/Data-Dictionary/SMR-Datasets/. Example taken from: Aldhous MC, Bhatia R, Pollock R et al. HPV infection and pre-term birth: a data-linkage study using Scottish Health Data. Wellcome Open Res 2019, 4:48 (https://doi.org/10.12688/wellcomeopenres.15140.1) |
3.2 You must include a citation for the dataset and add it to your reference list
The dataset you have reused should be cited in the body of your article, and you should add the dataset to your reference list as you would any other bibliographic citation.
You may use your preferred referencing style but should include, at a minimum:
Dataset creator; Publication year; Dataset title; Name of repository where the data is located; Persistent Identifier (e.g. DOI, ARK, URN etc.)
Please add [Data] to the reference to denote its type.
4. Further Guidance on Accessible Source Materials
4.1 You must provide a data availability statement as a section within your article, describing where the source materials are located and how they can be accessed by others
You must include a data availability statement at the end of your article, which can be used to describe any source materials which underpinned your study. While you will not be in control of how these sources have been made available, you should make it as easy as possible for others to find and identify your source materials.
The data availability statement should be added before the references list and describe the source materials you used, where they can be found, any relevant identifiers (such as archival accession numbers, call numbers for library special collections, or Object IDs for museum collections), and if available, copyright and licensing information. Any additional information on restrictions or conditions related to access should also be included.
Please include information relating to either physical or digital resources, depending on what you have used.
When drafting the statement, please include:
- The name of the repository, archive, museum, library, gallery or other location of the source materials;
- A brief description of the source materials you have used;
- Any available identifiers for the source materials;
- Any additional information on how the source can be accessed or restrictions related to access.
Examples:
| Data Type | Data Availability Statement Example | Data Citation Example |
| Data in a national library collection | The sources of newspapers in our research exist and can be referred to by other researchers at the Jakarta National Library using their website https://www.perpusnas.go.id/ or contact the email below materjilperpusnas20@gmail.com The librarian on duty will answer the email sent to this email address. In addition, these sources can also be seen (offline access only) at the North Sumatra Press Museum, Sei Alas Road No. 6, Medan. The Medan History House, Kota Cina/Pematang Siombak Road, No. 65, Neighborhood 7, Paya Pasir Village, Medan Marelan District, Medan 20250. The Center for the Study of History and Social Sciences (PUSSIS) Universitas Negeri Medan, Willem Iskandar Road, Pasar V, Medan Estate. | Example taken from: Azhari I, Sidiq R and Purnamasari I. The role of newspapers published in North Sumatra during Indonesia’s independence struggle between 1916-1925: A discourse. F1000Research 2022, 11:249 (https://doi.org/10.12688/f1000research.53442.2) |
| Data from an archival collection |
The collection used for this paper, The Papers of Victor Webb, is held by University of Glasgow Archives and Special Collections. The catalogue is available online: https://archiveshub.jisc.ac.uk/search/archives/e81a4437-f0b2-33ad-8229-ef4fc8a0cfdf. You can access the papers by making an appointment in the Searchroom here: https://www.gla.ac.uk/myglasgow/archives/contact/searchroombookingform/. A small number of records in this collection are subject to Data Protection legislation as they contain sensitive information; however, access may be given to bona fide researchers and academics. Please contact the Duty Archivist for advice on how to apply for access to these files (enquiries@archives.gla.ac.uk). |
Example taken from: Connelly H. A place to grow: Well-being and activism on Edinburgh’s post-war allotments and how this can inform urban gardening in Scotland today]. Wellcome Open Res 2019, 4:72 (https://doi.org/10.12688/wellcomeopenres.15216.1) |
| Archaeological excavation report | DIGITAL.CSIC: Mortella III wreck (1527, Corsica, France). Excavation report of the year 2019. 6th field campaign (22sd September to 22sd October 2019), Arrêté n°2019-308, OA3873 http://hdl.handle.net/10261/245875 (Cazenave de la Roche et al., 2020d) |
Cazenave de la Roche A: Artifacts inventory of the Mortella III wreck: General inventory of the artifacts from the excavations of the Mortella III wreck between 2010 and 2020 (Version 1) [Data set]. Digital CSIC. 2020a. http://hdl.handle.net/10261/249259 Example taken from: Cazenave de la Roche A, Ciacchella F, Langenegger F et al. Review of the research programme on the Mortella III wreck (2010-2020, Corsica, France): A contribution to the knowledge of the Mediterranean naval architecture and material culture of the Renaissance. Open Res Europe 2022, 2:6 (https://doi.org/10.12688/openreseurope.13942.1) |
| Bioarchaeological data |
All underlying data related with this manuscript are available in the ArtEmpire database that can be queried at the URL: https://artempire.cica.es/. This project utilised the following underlying data: https://artempire.cica.es/archeo/excavations/50. Description of data: Archaeological and bioarchaeological dataset of the burials excavated in the main nave of Panama Viejo’s cathedral in 2017. https://artempire.cica.es/archeo/excavations/55. Description of data: Archaeological and bioarchaeological dataset of the burials excavated in the atrium of Panama Viejo’s cathedral in 2017. https://artempire.cica.es/archeo/excavations/53. Description of data: Archaeological and bioarchaeological dataset of the burials excavated in the south-east of Panama Viejo’s Main Square in 2018. https://artempire.cica.es/archeo/excavations/54. Description of data: Archaeological and bioarchaeological dataset of the burials excavated in the south-east of Panama Viejo’s Main Square in 2018. |
Example taken from: Rivera-Sandoval J. Conditions of life and death at Panama Viejo: a bioarchaeological study of human skeletal remains (1519-1671). Open Res Europe 2021, 1:88 (https://doi.org/10.12688/openreseurope.13873.1) |
4.2 You must include a citation for the dataset and add it to your reference list
In line with existing referencing standards, all sources used must be cited in the body of the article and added to the reference list.
Depending on the citation style you are using, guidance may be provided for citing different types of source materials. For example, APA provides extensive guidance on citing archival sources.
Current best practice guidance for citing heritage collections recommends that you should cite the digital or physical version of a source, depending on what you used. If citing a digital collection, include a persistent identifier rather than a URL if available. For further information see: How to provide recommended citations for cultural heritage items?
You may use your preferred referencing style but should include the following elements, if available:
Creator of the materials; Year of creation; Name of the object or collection (if provided); Location of the materials; Persistent Identifier (e.g. DOI or other identifier such as accession number).
Please add [Data] to the reference to denote its type.
5. Limited exceptions to these guidelines
Ethical and security considerations
If data access is restricted for ethical or security reasons, please use your data availability statement to include a description of the restrictions on the data and all necessary information required for a reader or reviewer to apply for access to the data and the conditions under which access will be granted.
Data protection and participant privacy
Where human data cannot be sufficiently de-identified to protect participant privacy, we recommend depositing the data into a controlled access repository if your ethical approval permits you to do so.
If you cannot share the data in a repository, please include in your data availability statement: an explanation of the data protection concern; what, if anything, the relevant Institutional Review Board (IRB) or equivalent said about data sharing; and, where applicable, all necessary information required for a reader or reviewer to apply for access to the data and the conditions under which access will be granted.
Large data
Where data is too large to be feasibly hosted by a Gates Open Research approved repository, please include all necessary information required for a reader or reviewer to access the data alongside a description of this process in your data availability statement.
Data under license by a third party
In cases where data has been obtained from a third party and restrictions apply to the availability of the data, the data availability statement must include: all necessary information required for a reader or reviewer to access the data by the same means as the authors; and publicly available data that is representative of the analysed dataset and can be used to apply the methodology described in the article.
If you are unable to share your data for any reason not included here, or have additional questions about data sharing, please let our editorial team know and we will be happy to advise.
6. The FAIR Data Principles
Gates Open Research endorses the FAIR Data Principles as a framework to promote the broadest reuse of research data.
Additional, practical guidance can be found on the GoFAIR website.
Findable
Findable data should be easy for both humans and machines to find.
Findable data requires that:
F1. (Meta)data are assigned a globally unique and persistent identifier.
F2. Data are described with rich metadata (defined by R1 below).
F3. Metadata clearly and explicitly include the identifier of the data they describe.
F4. (Meta)data are registered or indexed in a searchable resource.
The best way to achieve Findable data is by:
- Depositing your dataset into a recognized data repository which assigns globally unique persistent identifiers (such as DOIs).
- Add as much contextual information (metadata) as possible when depositing your dataset into the repository.
Accessible
Accessible data refers to data that can be accessed once found; this may involve authentication of the user and authorization of access.
Accessible data requires that:
A1. (Meta)data are retrievable by their identifier using a standardized communications protocol
A1.1 The protocol is open, free, and universally implementable
A1.2 The protocol allows for an authentication and authorization procedure, where necessary
A2. Metadata are accessible, even when the data are no longer available
The best way to achieve Accessible data is by:
- Depositing your dataset into a recognized data repository which uses standard communications protocols like http://.
- Ensuring that the data repository you choose gives continued access to metadata even when datasets are removed.
Interoperable
Interoperable data refers to data that can be compared and combined with data from different sources, by both humans and machines.
Interoperable data requires that:
I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (Meta)data use vocabularies that follow FAIR Principles
I3. (Meta)data include qualified references to other (meta)data
The best way to achieve Interoperable data is by:
- Checking FAIRsharing.org for the standards that apply to your data type and using them.
- Ensuring that the data repository you choose allows you to include links or references to other related data.
- Using open, non-proprietary file formats for your data.
Reusable
Sharing data which can be reused by others is the main goal of the FAIR Principles.
Reusable data requires that:
R1. (Meta)data are richly described with a plurality of accurate and relevant attributes
R1.1. (Meta)data are released with a clear and accessible data usage license
R1.2. (Meta)data are associated with detailed provenance
R1.3. (Meta)data meet domain-relevant community standards
The best way to achieve Reusable data is by:
- Adding as much contextual information (metadata) as possible when depositing your dataset into a repository.
- Applying an open license to your data, preferably CC0 or CC-BY 4.0.
- Checking FAIRsharing.org for the standards that apply to your data type and using them.
7. Gates Open Research-approved repositories
Below is a list of repositories that have already been approved for hosting data alongside a Gates Open Research article.
If you are an author who wishes to use a repository not already on this list, please contact us. If you manage a repository and would like to be included on the list, please complete our Repository Evaluation form and return it to us.
General data, research materials and supporting documents
| Data Type | Where To Submit* | What To Include In The Data Availability Section Of Your Article |
| Any | B2Share† | Title, DOI |
| Any | Dryad | Title, DOI |
| Any, but especially data in SAV and POR formats | Dataverse | Title, DOI |
| Any | Figshare$ | Title, DOI |
| Any, but especially deposits with mixed data, materials and documents | Open Science Framework† | Title, DOI |
| Any, but especially deposits with mixed data and code | Zenodo | Title, DOI |
| Deposits of mixed data and code | Code Ocean | Title, DOI, embed code for interactive reanalysis tool |
* Please note that many repositories have a limit on the size (usually 2 or 5 GB) of single file uploads and charge for larger data files.
$ If you think your data are suitable for visualization within your article through the Figshare viewer, please contact us.
† Deposits must be made public and your project must be registered to ensure that a record will remain persistent and unchangeable.
$ If you think your data are suitable for visualization within your article through the Figshare viewer, please contact us.
† Deposits must be made public and your project must be registered to ensure that a record will remain persistent and unchangeable.
Software & source code
| Data Type | Where To Submit* | What To Include In The Data Availability Section Of Your Article |
| Latest source code | GitHub , BitBucket, SourceForge or Google Code | URL |
| Archived source code | Zenodo | Title, DOI and license* used |
| Deposits of mixed data and code | Code Ocean | Title, DOI, embed code for interactive reanalysis tool |
| Software | Authors may host software where they wish, though it is strongly recommended to use a stable URL | URL |
* An open license must be assigned and we strongly advise authors to use an OSI-approved license.
Humanities and social science data
* Deposits must be open access.
| Data Type | Where To Submit | What To Include In The Data Availability Section Of Your Article |
| Any | DANS-EASY* | Title, DOI |
| Any, but reserved for ISCPR member institutions | Open ICPSR | Title, DOI |
| Any | UK Data Archive* | Title, DOI |
| Social and economic data | UK Data Service | Title, DOI |
| Qualitative social science data | The Qualitative Data Repository | Title, DOI |
| Language data | Any appropriate CLARIN repository | Title, DOI |
| Archaeology data | ADS UK | Title, DOI |
| Demographic data | DSDR | Title, DOI |
Transcript data
Qualitative data resulting from recordings of interviews or focus group discussions should be anonymised by redaction and uploaded to a general data repository (see above). If it is not possible to anonymise the data sufficiently by redaction, a restricted route of data access should be provided by the authors and a comprehensive statement must be added to the Data Availability section of the article. If the transcript data cannot be shared under any circumstances, please contact the editorial team, who will be able to advise you.