Research Data Policy

Emergent Life Sciences Research (ELSR) supports transparency, reproducibility, and responsible management of research data.

Authors are encouraged to make research data available whenever reasonably possible and appropriate, while respecting ethical, legal, confidentiality, data protection, intellectual property, and other legitimate restrictions.

All manuscripts submitted to ELSR should include a Data Availability Statement describing whether and how the data supporting the research findings may be accessed.

Authors remain responsible for the accuracy, integrity, appropriate management, and transparent reporting of research data associated with their work.

 

1. Purpose of the Research Data Policy

The purpose of this policy is to support:

• Transparency in scientific research.
• Reproducibility and verification of research findings.
• Responsible research-data management.
• Appropriate reuse of research data.
• Accurate reporting of the origin and availability of data.
• Protection of confidential, sensitive, or restricted information.
• Integrity of the published scientific record.

ELSR recognizes that research data differ across scientific disciplines and that a single data-sharing model may not be appropriate for every study.

Data availability requirements are therefore considered in the context of the research, applicable ethical and legal obligations, and legitimate restrictions.

 

2. Definition of Research Data

The purpose of this policy, research data as materials, records, observations, measurements, or information used to support the findings reported in a scholarly work.

Research data may include, where relevant:

• Experimental measurements.
• Observational data.
• Field data.
• Laboratory data.
• Phenotypic data.
• Genotypic data.
• Genomic data.
• Transcriptomic data.
• Proteomic data.
• Metabolomic data.
• Soil and environmental data.
• Microbiological data.
• Survey data.
• Images used as research evidence.
• Instrument-generated outputs.
• Statistical datasets.
• Computational outputs.
• Simulation data.
• Code or scripts necessary to reproduce an analysis.
• Other materials that support the reported findings.

The nature of relevant research data will depend on the study and scientific discipline.

 

3. General Principle of Data Availability

Authors are encouraged to make data supporting the findings of their research available whenever reasonably possible.

Data sharing should support scientific transparency without violating legitimate ethical, legal, contractual, confidentiality, or intellectual property obligations.

ELSR does not require all research data to be publicly available in every circumstance.

Where data cannot be made publicly available, authors should provide an appropriate explanation in the Data Availability Statement.

The absence of public data access does not automatically prevent publication when a legitimate restriction exists.

 

4. Data Availability Statement

All manuscripts submitted to ELSR should include a Data Availability Statement.

The statement should clearly describe the availability of data supporting the findings of the manuscript.

The Data Availability Statement should indicate, as applicable:

• Whether data are included in the article.
• Whether data are included in supplementary material.
• Whether data have been deposited in a repository.
• The name of the repository.
• A DOI, accession number, or other persistent identifier where available.
• Whether data are available from the corresponding author.
• Whether reasonable conditions apply to data access.
• Whether data are subject to ethical, legal, confidentiality, or other restrictions.
• Whether no new data were generated or analyzed.

The statement should accurately reflect the actual availability of the data.

5. Examples of Data Availability Statements

Authors may adapt the following statements to reflect the circumstances of their research.

Data Included in the Article

“All data generated or analyzed during this study are included in this published article.”

Data Included in the Article and Supplementary Material

“All data supporting the findings of this study are included in the article and its supplementary material.”

Data Available on Reasonable Request

“The data supporting the findings of this study are available from the corresponding author upon reasonable request.”

Data Deposited in a Public Repository

“The dataset supporting the findings of this study has been deposited in [Repository Name] and is available under [DOI/accession number/persistent identifier].”

Restricted Data

“The data supporting the findings of this study are not publicly available because of [ethical/legal/confidentiality/contractual] restrictions. Information regarding appropriate data access may be obtained from the corresponding author.”

Third-Party Data

“The data analyzed in this study were obtained from [source]. Access to the data is subject to the conditions of the original data provider.”

No New Data

“No new data were generated or analyzed in this study.”

Authors should not use a standard statement that does not accurately describe the data associated with the manuscript.

 

6. Public Data Repositories

Where appropriate, authors are encouraged to deposit research data in a recognized repository.

A suitable repository should, where reasonably possible:

• Provide stable access to research data.
• Support appropriate metadata.
• Provide a persistent identifier or accession number.
• Clearly identify data access conditions.
• Support long-term discovery or preservation.
• Apply appropriate disciplinary or institutional standards.

Discipline-specific repositories may be preferred when established repositories exist for the relevant data type.

General research data repositories may be used when an appropriate discipline-specific repository is not available.

Authors are responsible for selecting a repository appropriate to their data and research field.

 

7. Repository Information

When data are deposited in a repository, authors should provide sufficient information to allow readers to identify the dataset.

The manuscript should normally include:

• Repository name.
• Dataset title, where applicable.
• DOI, accession number, or persistent identifier.
• Relevant access information.

Where a dataset is cited as a scholarly research output, authors should include the dataset in the reference list in accordance with the ELSR Reference Style.

The final ELSR Reference Guide already provides a specific citation format for datasets and recognizes public datasets and trusted repositories as appropriate research sources.

 

8. Data Supporting the Main Findings

Authors should retain data necessary to support the principal findings and conclusions of the manuscript.

The data associated with the study should be sufficiently complete to allow appropriate scientific examination of the reported results.

Authors should not intentionally withhold data when doing so would materially misrepresent the research findings.

Where only selected data are presented in the manuscript, the selection should not create a misleading representation of the study.

Selective reporting, fabrication, falsification, or inappropriate manipulation of research data is inconsistent with ELSR publication standards.

The final Guide for Authors already defines fabrication, falsification, selective reporting, and inappropriate manipulation as data-integrity concerns and permits the Editorial Office to request original data or supporting documentation.

 

9. Raw and Processed Data

Authors should distinguish, where relevant, between:

• Raw data.
• Processed data.
• Analyzed data.
• Derived data.
• Summary data.

The type of data required to support a published finding may depend on the research question and methodology.

ELSR does not require routine public submission of every intermediate file generated during a research project. However, authors should retain sufficient original or underlying data to support the reported findings and to respond to reasonable editorial enquiries.

Where data processing materially affects the results, authors should describe the relevant procedures with sufficient clarity.

 

10. Data Integrity

Research data should be collected, recorded, stored, analyzed, and reported responsibly.

Authors must not:

• Fabricate data.
• Falsify data.
• Selectively alter data to create a misleading result.
• Omit material observations in a manner that misrepresents the findings.
• Misrepresent the origin of data.
• Present synthetic data as experimental data without disclosure.
• Inappropriately manipulate research records.

Data cleaning, normalization, transformation, exclusion, and other analytical procedures may be scientifically appropriate.

Where such procedures materially affect the analysis, they should be appropriately described in the manuscript.

 

11. Data Retention

Authors are responsible for retaining research data and relevant research records in accordance with applicable:

• Institutional requirements.
• Funder requirements.
• Ethical approvals.
• Legal obligations.
• Disciplinary standards.
• Research agreements.

ELSR does not prescribe a single universal data-retention period for all research disciplines.

Authors should retain sufficient supporting data for an appropriate period to allow reasonable examination of the published findings and to meet applicable research obligations.

The journal may request relevant data in connection with an editorial or research-integrity enquiry.

 

12. Data Requests During Editorial Assessment

The Editorial Office or the responsible Editor may request research data or supporting information during manuscript assessment when necessary.

Such requests may arise when:

• Data presentation requires clarification.
• Statistical results require examination.
• Image-integrity concerns arise.
• Questions are raised regarding data completeness.
• Potential duplication is identified.
• Research integrity concerns are reported.
• Additional information is necessary to evaluate the reliability of the manuscript.

Authors are expected to cooperate with reasonable editorial enquiries.

A request for data does not, by itself, indicate suspected misconduct.

 

13. Data Requests During Peer Review

Where necessary for scientific assessment, an Editor may request that authors provide relevant data or supporting material during peer review.

Reviewers should not independently contact authors to request unpublished data.

Requests should normally be communicated through the journal's editorial process.

Data provided for confidential peer review should be treated as confidential manuscript material.

Reviewers must not use unpublished data obtained through peer review for personal or professional advantage.

 

14. Confidential and Sensitive Data

Research data should not be made publicly available when disclosure would violate legitimate confidentiality or privacy obligations.

Restricted data may include:

• Identifiable participant information.
• Personal data.
• Confidential clinical or research records.
• Data protected by informed consent conditions.
• Data subject to institutional restrictions.
• Confidential commercial information.
• Protected traditional or community knowledge.
• Other sensitive information.

Authors should use appropriate anonymization, de-identification, controlled access, or other safeguards where relevant.

Public data sharing should not compromise participant or research-subject confidentiality.

 

15. Human Participant Data

Data involving human participants should be managed in accordance with applicable ethical approval, informed consent, institutional requirements, and data-protection obligations.

Authors should not publicly share identifiable participant data without appropriate authorization.

Where participant-level data cannot be made openly available, the Data Availability Statement should explain the restriction in an appropriate manner.

Authors should avoid including unnecessary personal information in manuscripts, supplementary files, or public repositories.

Data sharing should remain consistent with the conditions under which the data were collected.

 

16. Animal Research Data

Authors conducting animal research should retain data necessary to support the reported experimental findings.

Data sharing should be consistent with applicable ethical, institutional, and legal requirements.

Where data are deposited publicly, authors should provide sufficient metadata to support scientific understanding of the dataset.

Research records relating to animal experiments may be requested when relevant to an ethical or scientific concern.

 

17. Plant, Agricultural, and Environmental Research Data

ELSR encourages appropriate sharing of data arising from plant, crop, soil, agricultural, and environmental research.

Relevant data may include:

• Genotype information.
• Germplasm identifiers.
• Phenotypic measurements.
• Environmental conditions.
• Experimental treatments.
• Soil characteristics.
• Sampling information.
• Geographic information.
• Agronomic data.
• Molecular datasets.

Authors should provide sufficient contextual information to allow readers to understand the data.

Where precise geographic, genetic-resource, traditional-knowledge, conservation, biosecurity, or other sensitive information should not be openly disclosed, authors may apply appropriate restrictions and explain the limitation.

 

18. Genomic, Transcriptomic, Proteomic, and Other Omics Data

Where established public repositories exist for major molecular datasets, authors are encouraged to deposit relevant data in an appropriate repository.

This may apply to:

• Genomic sequence data.
• RNA sequencing data.
• Transcriptomic datasets.
• Proteomic datasets.
• Metabolomic datasets.
• Other large-scale molecular datasets.

The manuscript should provide relevant accession numbers or persistent identifiers where available.

Authors should ensure that repository information is accurate and that the deposited dataset corresponds to the data described in the manuscript. Where repository release is subject to a publication-related embargo, authors should ensure that the data becomes accessible in accordance with the repository's release procedures and the information provided to the journal.

 

19. Data Generated Using Public or Third-Party Sources

Authors using publicly available or third-party data should clearly identify the original data source.

Authors should comply with the applicable:

• Data licenses.
• Terms of use.
• Access agreements.
• Citation requirements.
• Ethical restrictions.

The manuscript should distinguish between data generated by the authors and data obtained from other sources.

Use of third-party data does not transfer ownership of the original data to the authors. Where access restrictions apply, authors should not redistribute data in violation of the original provider's conditions.

 

20. Data Reuse and Secondary Analysis

ELSR considers research based on existing datasets when the study provides an appropriate scientific contribution.

Authors conducting secondary analysis should:

• Identify the original data source.
• Cite the dataset or relevant source.
• Describe the new analytical approach.
• Clearly distinguish previous findings from the new analysis.
• Comply with applicable data-use conditions.

Previously available data should not be presented as newly generated research data.

Where the same dataset has been used in related publications, authors should disclose relevant overlap where necessary.

 

21. Statistical and Computational Reproducibility

Authors should describe statistical and computational procedures with sufficient clarity to support scientific understanding of the analysis.

Where appropriate, authors are encouraged to make available:

• Analysis scripts.
• Computational code.
• Statistical workflows.
• Relevant parameter settings.
• Software versions.
• Model information.

ELSR recognizes that not all code can be publicly shared because of licensing, institutional, security, or intellectual property restrictions.

Where code is essential to the principal findings but cannot be publicly shared, authors should explain relevant access limitations where appropriate.

 

22. Software and Code

Software and code developed as part of a research study may constitute an important research output.

Authors are encouraged to deposit relevant code in an appropriate repository where feasible.

The manuscript should identify software used in the research when necessary to understand or reproduce the methodology.

Authors are responsible for ensuring that code shared with the article does not contain any unlawful content:

• Third-party proprietary code.
• Confidential information.
• Access credentials.
• Personal data.
• Other restricted material.

Where a separate software license applies, it should be clearly identified.

 

23. Supplementary Data

Research data may be provided as supplementary material when appropriate.

Supplementary data should:

• Be relevant to the manuscript.
• Be accurately described.
• Use clear file names.
• Be presented in an accessible and understandable format were reasonably possible.
• Avoid unnecessary confidential or personal information.

Supplementary material forms part of the published scholarly record where it is formally published with the article.

ELSR may request revision, removal, or reorganization of supplementary files when necessary.

 

24. Data Formats and Documentation

Authors are encouraged to use data formats that support accessibility and reuse where reasonably possible.

Datasets should include sufficient documentation or metadata to allow readers to understand:

• The nature of the data.
• Variables or measurements.
• Units.
• Experimental treatments.
• Coding or abbreviations.
• Relevant analytical information.

Highly specialized data may require additional documentation.

The level of documentation should be proportionate to the complexity of the dataset.

 

25. Data Citation

Research datasets should be cited when they constitute a relevant source or research output.

Data citations should identify the dataset sufficiently to allow readers to locate it.

Where available, authors should include:

• Dataset author or creator.
• Year.
• Dataset title.
• Repository.
• DOI or persistent identifier.

Dataset citations should follow the official ELSR Reference Style.

 

26. Intellectual Property and Commercial Restrictions

Data sharing may be limited where legitimate intellectual property or commercial restrictions apply.

Examples may include:

• Pending patent applications.
• Contractual research restrictions.
• Confidential industry collaborations.
• Proprietary datasets.
• Technology-transfer requirements.

Authors should not make false or misleading claims of confidentiality solely to avoid reasonable scientific transparency.

Where access is restricted, the Data Availability Statement should describe the limitation appropriately without disclosing confidential information.

 

27. Data Related to Patents

Authors should consider intellectual property obligations before publicly depositing research data.

Public disclosure of data may affect patent or other intellectual property processes in some circumstances.

Authors are responsible for consulting their institution, technology-transfer office, funder, or appropriate professional adviser where necessary.

ELSR does not provide legal advice regarding patentability or intellectual property ownership.

A legitimate patent-related restriction should be appropriately reflected in the Data Availability Statement.

 

28. Data Licensing

Authors are encouraged to identify appropriate licensing conditions for publicly deposited research data.

The license applied to an ELSR article does not automatically override a separate license applied to a dataset, software, or code.

Where data are deposited in an external repository, the repository's licensing and access arrangements may apply.

Authors should ensure that the data license is consistent with their rights and applicable research obligations.

Copyright and licensing of published articles are addressed separately in the ELSR Copyright & Licensing Policy.

 

29. FAIR Data Principles

Where appropriate and reasonably achievable, authors are encouraged to manage and share research data in ways that support the principles of being:

• Findable.
• Accessible.
• Interoperable.
• Reusable.

Application of these principles may vary according to discipline, data type, infrastructure, ethical requirements, and available resources.

ELSR encourages good data-management practices but recognizes that full implementation may not be possible for every study.

 

30. Data and Artificial Intelligence

Where AI-assisted or machine-learning methods are used to generate, process, classify, or analyze research data, authors remain responsible for the validity and integrity of the resulting data and analyses.

AI-generated or synthetic data should be clearly identified.

Synthetic data must not be presented as genuine experimental or observational data.

Where AI-assisted data processing materially affects the research findings, the relevant methodology should be transparently described.

Additional requirements are provided in the ELSR AI and Generative AI Policy.

 

31. Data Fabrication and Falsification

Fabrication or falsification of research data is not acceptable.

Potential concerns may include:

• Inventing research observations.
• Creating false experimental measurements.
• Altering data to produce a desired outcome.
• Removing data without scientific justification to misrepresent results.
• Misrepresenting the origin of a dataset.
• Presenting fabricated computational outputs.
• Falsifying research records.

Data-integrity concerns will be assessed under the ELSR Publication Ethics Policy.

Serious concerns may result in rejection, post-publication action, or referral to an appropriate institution or authority.

 

32. Data Availability After Publication

Authors should seek to maintain the data-access conditions described in the published Data Availability Statement.

Where repository data are moved, corrected, withdrawn, or subject to a significant access change, authors should inform the Editorial Office when the change materially affects the published article.

If a published Data Availability Statement becomes materially inaccurate, ELSR may consider an appropriate correction.

Authors should not intentionally remove access to data after publication in a manner inconsistent with the published statement without legitimate justification.

 

33. Requests for Data After Publication

Readers may contact the corresponding author regarding data described as available upon reasonable request.

A reasonable request may depend on:

• The scientific purpose of the request.
• The nature and volume of the data.
• Ethical restrictions.
• Confidentiality.
• Data-protection requirements.
• Intellectual property.
• Existing research agreements.
• Technical feasibility.

A statement that data are available upon reasonable request should represent a genuine willingness to consider appropriate requests.

Authors should not use this statement when they do not intend to provide data under any circumstances.

ELSR does not normally act as a routine intermediary for individual data requests.

However, the journal may examine concerns where a published Data Availability Statement appears materially misleading.

 

34. Editorial Assessment of Data Concerns

When a concern regarding research data is raised, ELSR may:

• Request clarification from the authors.
• Request original or underlying data.
• Request research records.
• Request statistical outputs.
• Request repository information.
• Request information regarding data restrictions.
• Seek appropriate scientific or institutional information.

The journal will seek to evaluate data concerns fairly and on the basis of available information.

A failure to provide requested data does not by itself establish misconduct.

However, the journal may make an editorial decision based on the information reasonably available when relevant supporting information cannot be obtained.

 

35. Editorial Actions

Depending on the nature and seriousness of a data-related concern, ELSR may:

• Request clarification.
• Request correction of the Data Availability Statement.
• Request additional data information.
• Request manuscript revision.
• Suspend editorial evaluation.
• Reject the manuscript.
• Publish a correction.
• Publish an Expression of Concern.
• Retract a published article.
• Refer serious concerns to an appropriate institution or authority.

Post-publication action will be handled in accordance with the ELSR Corrections & Retractions Policy.

 

36. Research Data Policy Oversight

The Editor-in-Chief and Editorial Office are responsible for overseeing the implementation of this Research Data Policy.

ELSR may review and update its data procedures to reflect developments in open research, data repositories, research infrastructure, disciplinary practices, and responsible data management.

Authors are responsible for ensuring that the Data Availability Statement and research-data information provided to ELSR are accurate.

All manuscripts submitted to ELSR should comply with the applicable requirements of this Research Data Policy.