Data Sharing and Deposition

Last Updated: October 2026

ETFLIN supports responsible research data sharing and deposition to promote transparency, reproducibility, verifiability, and the reuse of scholarly research. This policy establishes the requirements for preparing, documenting, depositing, identifying, and maintaining access to research data associated with manuscripts submitted to ETFLIN journals.

The policy is informed by the FAIR Guiding Principles, which emphasize that research data should be Findable, Accessible, Interoperable, and Reusable. It also reflects the principles of data citation established by the FORCE11 Joint Declaration of Data Citation Principles and the expectations for data availability and reproducibility outlined in the COPE Core Practices.

ETFLIN recognizes that responsible data sharing does not require every dataset to be publicly accessible without restrictions. Legal obligations, ethical requirements, participant privacy, intellectual property rights, contractual restrictions, and legitimate security concerns may require controlled access or prevent public disclosure. Such restrictions must be justified and managed transparently.

Scope of Research Data

This policy applies to research data and associated materials that support the results, analyses, and conclusions reported in manuscripts submitted to ETFLIN journals.

Research data include information collected, observed, generated, or processed for the purpose of answering research questions or supporting scholarly conclusions. Depending on the discipline and research design, such materials may include:

Raw and processed experimental data, measurements, observations, and survey responses.
Quantitative and qualitative datasets, including relevant transcripts, coded records, and analytical outputs.
Images, microscopy data, spectra, chromatograms, sequence data, and other scientific measurements.
Data tables, supplementary datasets, statistical outputs, and other materials necessary to interpret reported findings.
Computational models, analytical scripts, source code, and other research outputs when they are necessary to understand, verify, or reproduce the reported analyses.
Relevant metadata, data dictionaries, codebooks, protocols, and documentation required to interpret and reuse a dataset.
Secondary datasets obtained from external repositories or other sources and used as a basis for the reported findings.

The scope of deposition must be proportionate to the research. Authors are expected to preserve and, where appropriate, share the data needed to support the principal claims and analyses of their articles. This does not mean that every intermediate file, temporary working document, or unrelated administrative record must be deposited.

Where data are too large, complex, heterogeneous, or technically difficult to share as a single package, authors may deposit them in multiple files or related collections, provided that the materials are clearly organized and their relationships are documented.

The application of this policy depends on whether a manuscript generates, collects, analyzes, or relies on research data. Editorials, opinion pieces, and other article types that do not generate or analyze research data are not automatically required to deposit a dataset. However, publicly available datasets or other research materials relied upon to support substantive claims should be appropriately identified and cited.

ETFLIN expects authors reporting original research to make the data underlying the principal findings available through an appropriate repository whenever sharing is legally, ethically, and technically permissible.

Public deposition is the preferred approach when it does not conflict with applicable restrictions. The deposited material should be sufficient to support meaningful examination of the findings and should include relevant documentation needed to interpret the data.

Authors should not withhold shareable data solely because they prefer to retain exclusive access, anticipate additional publications, or consider the data commercially valuable. Such circumstances do not automatically justify restricting access to data that are otherwise required to be shared under the applicable journal, institutional, or funding requirements.

Where public sharing is not possible or appropriate, authors must establish a legitimate basis for the restriction and consider whether an alternative arrangement is feasible. Depending on the circumstances, this may involve sharing a properly de-identified or aggregated dataset, depositing data in a controlled-access repository, providing a restricted access procedure, or identifying the authoritative source from which the data may be obtained.

A restriction on public access does not automatically exempt authors from documenting the existence, provenance, or location of the dataset. The relevant dataset should remain identifiable and its access conditions should be explained through the journal's applicable reporting procedures.

The requirements for describing the availability or restriction of data in the published article are provided separately in ETFLIN's Data Availability Statement Policy. This policy governs the underlying sharing and deposition practices rather than prescribing the wording of that statement.

Selection of Data Repositories

Authors should deposit research data in a repository appropriate to the discipline, nature, sensitivity, and intended reuse of the dataset.

A disciplinary or subject-specific repository should generally be preferred when it is well established and supports the data type being deposited. Examples include repositories for biological sequences, chemical data, clinical research, environmental observations, or other specialized scientific outputs.

Where an appropriate disciplinary repository is unavailable, authors may use a suitable institutional repository or a trusted general-purpose research data repository.

The Registry of Research Data Repositories (re3data) may be used to identify repositories relevant to a particular discipline or dataset. The presence of a repository in a registry should be considered alongside its actual policies, technical capabilities, access conditions, and suitability for the research data concerned.

A suitable repository should, as applicable:

Provide a stable landing page and a persistent identifier for the deposited dataset.
Support appropriate metadata, documentation, and data citation.
Clearly identify the repository operator and its policies regarding access, licensing, preservation, and reuse.
Offer access arrangements that are suitable for the sensitivity and legal status of the data.
Support version identification or other mechanisms for distinguishing updated datasets from earlier versions.
Provide reasonable measures to maintain the availability and integrity of deposited files and their associated metadata.

Authors should avoid repositories that lack clear ownership, access conditions, basic metadata, or a credible preservation arrangement. Depositing files on a personal website or attaching them to an informal file-sharing service should not be treated as equivalent to depositing them in a suitable research data repository.

An external repository's inclusion in a recognized directory does not guarantee that every deposit is suitable. Authors remain responsible for selecting a repository that meets the needs of the dataset.

Timing of Deposition and Availability

When public deposition is required or undertaken as part of the publication process, authors should prepare their datasets and supporting documentation as early as practicable, preferably during manuscript preparation or submission.

Unless a justified exception has been approved, required datasets must be deposited and accessible under their intended access conditions before the final article is published. This allows the editorial team to verify the supplied information and helps ensure that the published article provides a usable route to the supporting data.

Where a repository supports private reviewer links, temporary access credentials, or confidential review of a dataset, authors may use these mechanisms during peer review. Such arrangements must protect the confidentiality of the manuscript and dataset, and the final public or controlled-access record must be established as appropriate before publication.

Acceptance of a manuscript does not automatically mean that a required dataset has been deposited, verified, or made available. When the applicable requirements have not been satisfied, the editorial office may request the missing information or defer final publication until the issue has been resolved.

Embargoes may be appropriate in circumstances involving contractual obligations, legitimate intellectual property protection, coordinated release arrangements, or other substantiated reasons. Authors must identify the reason for the embargo, its expected duration, and the conditions under which access will begin.

An embargo must not be used merely to avoid legitimate data-sharing obligations. Where ETFLIN requires data to be available at publication, an embargo that prevents the required access must be reviewed and approved as an exception before the article proceeds to publication.

If an external repository or other restriction prevents timely public release, authors must inform the editorial office and explain the circumstances before publication. Approval of a restriction is not automatic and depends on the justification and applicable requirements.

Persistent Identification and Data Citation

Deposited datasets must be identifiable through a persistent identifier where the repository provides one. Suitable identifiers may include a Digital Object Identifier (DOI), an accession number, or another persistent identifier recognized by the relevant data community.

A DOI is preferred where available and appropriate, but ETFLIN does not require every data type to use a DOI if an established disciplinary repository provides another persistent identifier.

Authors must cite datasets that directly support the claims or analyses in their articles. Data citations should be sufficiently complete to allow readers to identify the dataset, its creators, the publication or release date, its repository, and the specific version used, where applicable.

The FORCE11 Joint Declaration of Data Citation Principles emphasizes the importance of credit, persistent identification, accessibility, provenance, and version-specific verification in data citation. Consistent with these principles, a dataset should be treated as a citable research output rather than merely an unreferenced supplementary file.

Where a dataset is deposited specifically to support an article, its citation should be included in the manuscript's reference list or another appropriate location permitted by the journal's publication format. The article and dataset should be connected through their available persistent identifiers and repository metadata.

If a repository provides version-specific identifiers, authors should cite the version that corresponds to the data used to produce the reported findings. If no version-specific identifier is available, the cited record should include sufficient information to establish which dataset version was used.

Authors must not cite an identifier that leads to an unrelated, inaccessible, or materially different dataset. If the repository record changes or the dataset is updated, the relationship between the original data, revised versions, and associated publication should remain traceable.

Dataset Documentation and Metadata

Deposited datasets must be accompanied by sufficient documentation to allow qualified users to understand their content, structure, origin, and intended interpretation.

Depending on the type of data, appropriate documentation may include:

A dataset title and concise description of its purpose and contents.
The names of the creators or responsible research group.
The data collection period, geographical or experimental context, and relevant methodology.
Definitions of variables, abbreviations, units of measurement, and coding conventions.
A data dictionary or codebook where necessary.
Explanations of missing values, exclusions, data transformations, and relevant processing decisions.
The provenance of reused or derived data and the relationship between raw and processed datasets.
Details of applicable licenses, access restrictions, and conditions for reuse.

The level of documentation should be proportionate to the complexity of the data. A small experimental dataset may require only a concise README file and clear variable definitions, whereas a large or complex dataset may require a more extensive data dictionary, protocol documentation, or supplementary files.

Where an established community standard exists for a specific data type, authors should use it when appropriate. Data should not be deposited in a way that prevents meaningful interpretation simply because the files are technically downloadable.

ETFLIN encourages the use of interoperable and widely supported file formats where suitable. However, no single format is appropriate for all research disciplines. Authors should prioritize formats that preserve the relevant information and allow reasonable access with commonly available software, while retaining specialized native files when these are necessary to preserve scientific accuracy.

The FAIR principles require that data and metadata be sufficiently documented, discoverable, accessible under clearly defined conditions, and suitable for reuse. FAIR compliance does not require every dataset to be completely open, nor does it excuse the omission of necessary metadata or documentation.

Data Integrity, Provenance, and Version Control

Authors are responsible for ensuring that deposited data accurately represent the research outputs described in the manuscript and have not been manipulated or altered in a manner that misrepresents the findings.

Data preparation and processing must follow appropriate scientific practices. Necessary transformations, exclusions, normalization procedures, corrections, and other processing steps should be documented sufficiently to allow the resulting dataset to be interpreted and, where applicable, independently assessed.

Deposited data must be consistent with the tables, figures, analyses, and principal findings reported in the article. Material discrepancies between the dataset and the manuscript must be resolved before publication or explained transparently where they arise from legitimate differences in versions or analytical procedures.

When a dataset is updated after deposition, authors should use the repository's versioning system where available. Material updates should not silently overwrite a published dataset if doing so would compromise the ability of readers to identify the data originally used for the article.

Where a deposited dataset is corrected after publication, the authors should ensure that the repository record clearly identifies the relevant change and that the article's data references or associated records are updated when necessary.

The preservation of provenance and version information supports verification and reuse, consistent with the FAIR Guiding Principles and recognized principles for research data citation.

Depositing a dataset does not, by itself, establish that the data are accurate or that the reported conclusions are valid. ETFLIN may seek clarification, request relevant supporting records, or refer concerns for further assessment when credible discrepancies or research integrity issues arise.

Research data must be shared in compliance with applicable laws, research ethics approvals, participant consent requirements, contractual obligations, intellectual property rights, and other legitimate restrictions.

Authors must assess whether a dataset contains personal information, confidential records, sensitive commercial information, restricted government information, protected environmental information, or other content for which uncontrolled disclosure may cause harm.

Where a dataset contains information relating to human participants, authors should use appropriate de-identification, anonymization, aggregation, or other protective measures before sharing. Removing names or direct identifiers may not be sufficient when combinations of characteristics could allow participants to be re-identified.

Data that cannot be safely or lawfully released to the public should not be deposited in an unrestricted public repository. Where appropriate, authors should use a controlled-access repository or an established access procedure that permits legitimate research use while protecting confidentiality.

Access conditions should specify the requirements that apply to potential users, such as submitting an access request, demonstrating an appropriate research purpose, obtaining required authorization, or entering into a data-use agreement. Such requirements must be proportionate and should not be used to obstruct legitimate access without a valid basis.

Written consent is not, by itself, sufficient to authorize every form of disclosure. Data sharing must also comply with relevant laws, ethical approvals, the scope of consent originally obtained, and applicable institutional or contractual requirements.

Authors must explain any material restrictions on access and identify the reason for the restriction through the journal's applicable reporting process. Where only part of a dataset is sensitive, authors should consider whether a non-sensitive subset or appropriately transformed version can be shared.

These safeguards reflect the principle that responsible openness must be balanced with legitimate privacy, security, and confidentiality requirements. For additional guidance on sensitive research data, authors may consult Springer Nature's guidance on sensitive data.

Third-Party Data and Reuse Permissions

Authors who use data obtained from an external repository, institution, commercial provider, or another research group must ensure that the data were obtained and reused lawfully and in accordance with the applicable licensing and access conditions.

Public availability does not automatically permit unrestricted redistribution. Before depositing third-party data, authors must verify whether the relevant license, data-use agreement, contractual arrangement, or repository policy permits the proposed form of sharing.

Where redistribution is prohibited, the authors should not upload the restricted dataset to another repository. Instead, they should cite the authoritative source, identify the applicable persistent identifier or accession number where available, and explain any relevant access restriction through the journal's applicable reporting process.

Where an article combines data from different sources, authors must identify the relevant sources and distinguish original data generated by their research from reused data obtained elsewhere.

Authors must not remove attribution, alter license information, or imply ownership of data that belong to another party. Where permissions are required, they must be obtained before deposition.

ETFLIN may request clarification or supporting evidence if the rights to deposit or redistribute a dataset are uncertain.

Research Software, Code, and Associated Materials

When scripts, source code, computational models, or specialized software are necessary to understand or reproduce the analyses reported in an article, authors are encouraged to make those materials available alongside the associated data whenever legally and technically permissible.

The deposited materials should include sufficient documentation to explain their purpose and use. Where appropriate, authors should identify relevant software versions, dependencies, execution requirements, parameters, and other information necessary to interpret the computational workflow.

Code and software should be deposited in a suitable repository or archived through a service that supports persistent identification and version control. Where the code is linked to a specific dataset or publication, the relationship should be documented clearly.

Authors must comply with applicable licenses and third-party restrictions. ETFLIN does not require authors to disclose protected credentials, confidential infrastructure details, proprietary source code that they are not authorized to release, or other restricted information. Where access is limited, authors should explain the relevant restriction and identify what supporting information can legitimately be provided.

Sharing code does not replace the obligation to make the underlying research data available where required. Conversely, a dataset may still be useful even when the software needed to process it cannot be publicly released, provided that the limitation is documented and the available evidence can be evaluated appropriately.

Data Management Planning

Authors should prepare a Data Management Plan (DMP) appropriate to the scale, complexity, and sensitivity of their research data. A DMP may describe the types of data generated or reused, storage arrangements, documentation, access controls, licensing, responsibilities, preservation, and intended deposition.

A comprehensive DMP is particularly relevant to data-intensive projects, projects involving sensitive or restricted datasets, studies supported by funders with data management requirements, and research involving multiple institutions or data sources.

ETFLIN does not automatically require a full DMP for every manuscript, particularly where the publication does not generate or analyze research data. However, the editorial office may request a DMP or relevant portions of it when necessary to assess the feasibility of data sharing, the adequacy of documentation, compliance with stated funding conditions, or the handling of restricted data.

Where an institution or funder requires a DMP, authors remain responsible for complying with that requirement. Submitting a DMP does not replace the obligation to carry out the stated data management practices or to deposit and document the relevant data as required by this policy.

DMP documentation may be requested confidentially during editorial assessment when it contains information that is not intended for public disclosure. Such requests are intended to verify responsible data stewardship and should be limited to information relevant to the manuscript.

Editorial Verification and Compliance

ETFLIN may verify the existence, accessibility, and identification of deposited datasets as part of the editorial process. Verification may include checking persistent identifiers, repository records, access permissions, supporting documentation, and the consistency of cited data with the manuscript.

Where data sharing is required, the editorial office may request that the authors provide the relevant repository link, accession number, access credentials for confidential review, or other information needed to inspect the dataset.

Reviewers and editors may request access to supporting data when necessary to evaluate the methods or findings of a manuscript. Any such access must respect applicable confidentiality, privacy, and access restrictions.

If required data have not been deposited, relevant documentation is missing, or the stated access arrangements are not functioning, ETFLIN may request correction or clarification before proceeding with publication. The editorial office may defer final publication when a material requirement remains unresolved and no acceptable exception has been established.

An administrative check of a repository link or dataset does not constitute a guarantee that all reported results can be independently reproduced or that a dataset is scientifically valid. Authors remain responsible for the accuracy, completeness, and lawful handling of their research data.

Exceptions and Restricted Deposition

ETFLIN recognizes that some datasets cannot be made openly available for legitimate reasons. Such circumstances may include privacy and confidentiality obligations, ethical restrictions, restrictions imposed by lawful data-use agreements, intellectual property limitations, national security considerations, or other demonstrable legal and technical constraints.

Authors seeking an exception to an applicable sharing or deposition requirement must provide a clear explanation of the restriction. Where possible, they should identify alternative arrangements that preserve a reasonable level of transparency, such as controlled access, de-identified data, aggregated data, metadata-only records, or access through the original data custodian.

Exceptions are assessed on a case-by-case basis. ETFLIN may request clarification or supporting information to determine whether the proposed restriction is justified and whether an alternative form of access is feasible.

A lack of a convenient repository, a preference to retain exclusive control over otherwise shareable data, or a general assertion of confidentiality is not automatically sufficient to justify withholding data required by the applicable policy.

Where only a limited portion of a dataset is restricted, authors should consider sharing the remaining non-sensitive material when feasible. The scope of the exception should be proportionate to the actual restriction rather than applied indiscriminately to all data generated by the research.

Approval of an exception does not waive other applicable obligations concerning the accurate reporting of methods, results, and research limitations.

Long-Term Accessibility and Repository Limitations

Authors should choose repositories that provide reasonable support for persistent identification, metadata retention, and continued access. However, ETFLIN cannot guarantee that every external repository will remain operational indefinitely or that every deposited file will always be available.

If a repository becomes unavailable, a dataset is moved, or a persistent identifier no longer resolves correctly, authors should make reasonable efforts to restore the link or provide an alternative route to the dataset.

Where feasible, the updated location should maintain the relationship with the original persistent identifier and preserve the bibliographic identity and version information of the dataset. Material changes must not obscure which data were used in the published research.

If data accessibility becomes materially different from what was stated in a published article, the authors should inform the editorial office so that the appropriate record or access information can be reviewed and updated where necessary.

The long-term preservation of published articles and associated publication records is governed by ETFLIN's separate archival arrangements. This policy concerns the responsible deposition and continued identification of research data, including data held by external repositories.

Relationship with Data Availability Reporting

Authors must report the availability and access conditions of relevant research data in accordance with ETFLIN's Data Availability Statement Policy.

This policy governs the underlying data-sharing and deposition practices, including repository selection, documentation, permissions, persistent identification, and appropriate restrictions. The Data Availability Statement policy governs how the availability or unavailability of data is communicated in the published article.

The two requirements are complementary. A statement identifying a dataset does not replace a required deposition, and depositing a dataset does not remove the obligation to describe its availability accurately in the manuscript.

Suspected Data Misconduct and Inaccurate Deposits

Concerns regarding fabricated, falsified, manipulated, or materially misrepresented datasets must be distinguished from ordinary technical or documentation deficiencies.

If ETFLIN identifies credible indications that deposited data do not correspond to the reported findings, have been deliberately altered to misrepresent the results, or have been made unavailable contrary to a material publication commitment, the journal may request clarification and relevant supporting records.

Where the concern cannot be resolved through an ordinary correction or clarification, ETFLIN may refer the matter for further assessment under the applicable publication ethics procedures. Any action affecting the published record must be proportionate to the evidence and the significance of the concern.

An incomplete metadata record or a broken repository link does not, by itself, establish research misconduct. The nature of the issue, the response of the authors, and the implications for verification of the published findings must be considered before deciding on further action.

Policy Review

ETFLIN will periodically review this policy to maintain consistency with recognized data-sharing practices, developments in research data infrastructure, and relevant ethical and legal requirements.

The journal may revise its requirements as repository standards, data management practices, and disciplinary expectations evolve. Material changes will be reflected in the published policy.

Questions regarding research data sharing and deposition may be directed to halo@etflin.com.