# Data Sharing in Life Science Research ## Quick Answer - A data availability statement tells readers where and how they can access the data supporting your published findings, and journals increasingly require one. - Choose a recognized repository for your data type, obtain a persistent identifier such as a DOI, and cite the dataset within your statement. - A statement that says "data available upon request" is often noncompliant with funder policies and may be rejected by journals. ## Why Data Availability Statements Matter in Life Science Research Life science research depends on the ability of other investigators to verify, reproduce, and extend published findings. A data availability statement is the formal declaration in a manuscript that describes whether the data underlying the study are accessible, where they are stored, and under what conditions they can be obtained. This statement has moved from a discretionary courtesy to a standard expectation in most peer-reviewed journals and a formal requirement under many funding policies. The Committee on Publication Ethics identifies data handling as a core practice for journals and publishers. Their guidance addresses how journals should manage data sharing, including the expectation that authors provide access to data that support their published claims. Journals that follow these practices will typically require a data availability statement at submission. The [COPE Core Practices](https://publicationethics.org/core-practices) describe the responsibilities of authors, reviewers, and editors in maintaining the integrity of the published record, and data access is a central part of that responsibility. Funding agencies have also established explicit expectations. The National Institutes of Health Data Management and Sharing Policy requires researchers to submit a data management and sharing plan with their grant applications and to follow that plan during the award period. The [NIH Data Management and Sharing Policy](https://sharing.nih.gov/data-management-and-sharing-policy) describes the expectation that data be shared in a manner that is consistent with the plan and with applicable laws and regulations. For researchers funded by NIH, the data availability statement in a publication is the visible outcome of that planning process. The practical problem for many researchers is that journal policies vary. Some journals require a statement for every manuscript. Others accept a statement that says no new data were generated. Some journals require data to be deposited in a specific repository, while others allow supplementary files. A statement that satisfies one journal may be rejected by another. The purpose of this article is to explain the components of a data availability statement, the common scenarios you will encounter, and the decisions you need to make to comply with both journal and funder requirements. ## At a Glance The table below summarizes the common scenarios for data availability statements and the recommended approach for each. | Scenario | What to Write | Repository or Location | Common Pitfall | | --- | --- | --- | --- | | Original data generated in your study | State that data are deposited in a named repository and provide the persistent identifier | Domain repository such as NCBI, Dryad, Figshare, or institutional repository | Omitting the DOI or accession number | | Reanalysis of existing public data | State that the study used publicly available data and cite the original dataset | The original repository where the data are held | Failing to cite the original dataset and its version | | No new data generated | State that the study used no new data and describe what was used | Not applicable | Writing a vague statement that does not say what was used | | Data available upon request | State that data are available from the corresponding author | Not a repository | Many funders and journals do not accept this option | ## Core Principles of Data Availability Statements ### Transparency as the Foundation The purpose of a data availability statement is transparency. A reader should be able to determine, without contacting the author, whether the data that support the conclusions are accessible. The statement should be specific enough that a reader can locate the data without further correspondence. This means naming the repository, providing the identifier, and describing the conditions of access if any. The EQUATOR Network provides reporting guidelines for health research that emphasize transparent reporting. The [EQUATOR Network](https://www.equator-network.org/) is a resource for selecting the appropriate reporting guideline for your study type. While reporting guidelines focus on methods and results, they also address data availability in many cases. The principle is the same: the reader should be able to assess the evidence behind the claims. ### The Difference Between Data Availability and Data Accessibility Data availability means the data exist and are stored somewhere. Data accessibility means the data can be obtained by a reader. A statement that says "data are available from the corresponding author" may be true in the sense that the data exist, but it does not guarantee accessibility. The reader must request the data and wait for a response. The author may be unavailable, may decline, or may take months to respond. This is why many journals and funders now require data to be deposited in a repository instead of held by the author. The NIH Data Management and Sharing Policy expects data to be shared in a timely manner and in a way that is consistent with the plan. The [NIH policy](https://sharing.nih.gov/data-management-and-sharing-policy) describes the expectation that data be shared through established repositories where possible. This is a practical shift from the older model of data on request. ### The Role of Persistent Identifiers A persistent identifier is a long-lived reference to a digital object. The most common type is the Digital Object Identifier, or DOI. A DOI is assigned by a registration agency and is permanently linked to the dataset. When you cite a dataset in your data availability statement, you should provide the DOI or accession number so the reader can go directly to the data. The choice of repository determines the type of identifier you will receive. Some repositories assign DOIs, others assign accession numbers. For example, NCBI repositories such as GEO and SRA assign accession numbers. Generalist repositories such as Zenodo and Figshare assign DOIs. The statement should include the identifier exactly as provided by the repository. ## How to Write a Data Availability Statement ### Step 1: Determine What Data You Have Before you write the statement, you need to inventory the data that supports your findings. This includes raw data, processed data, analysis scripts, and any other digital artifacts that are necessary to reproduce the results. The data may include sequence files, microscopy images, flow cytometry files, spreadsheets, or code. The statement should cover the data that is needed to verify the conclusions. ### Step 2: Choose a Repository The choice of repository depends on the data type and the journal requirements. Domain repositories are preferred when they exist. For example, genomic data should go to NCBI repositories, protein data to the Protein Data Bank, and clinical data to a clinical data repository. When no domain repository exists, a generalist repository such as Zenodo or Figshare is acceptable. The NIH Data Management and Sharing Policy provides guidance on selecting repositories. The [NIH sharing policy](https://sharing.nih.gov/data-management-and-sharing-policy) describes the characteristics of a suitable repository, including the use of persistent identifiers, access controls, and preservation. The researcher should select a repository that meets these criteria. ### Step 3: Deposit the Data Deposit the data in the repository before you submit the manuscript. This is important because the repository will assign the identifier that you will include in the statement. Some journals allow you to deposit data and provide the identifier in the manuscript. Others require the data to be available at the time of submission. Check the journal instructions before you submit. ### Step 4: Write the Statement The statement should be concise and specific. It should name the repository, provide the identifier, and describe any conditions of access. The statement should be placed in the manuscript in the location specified by the journal, which is usually after the references or in a dedicated section. ### Step 5: Verify the Statement Before you submit, verify that the identifier works and that the data are accessible. This is a simple check that can prevent a compliance issue. If the data are under embargo, the statement should say so and provide the date when the data will be available. ## Templates for Common Scenarios ### Original Data Generated in the Study This is the most common scenario. You have generated new data and you need to state where it is available. The template is: "The data supporting the findings of this study are available in the [Repository Name] at [URL or DOI], accession number [Identifier]." For example, if you deposited sequence data in NCBI, the statement would name NCBI and provide the accession number. If you deposited a dataset in Zenodo, the statement would name Zenodo and provide the DOI. ### Reanalysis of Existing Public Data If your study uses data that were previously published and are available in a public repository, the statement should say so. The template is: "This study uses publicly available data from [Repository Name], available at [URL or DOI]. The original study is cited in the references." This scenario is common in meta-analyses and secondary analyses. The statement should identify the original dataset and its location. The reader should be able to find the data without contacting the author. ### No New Data Generated If your study is a review, a perspective, or a theoretical paper, you may have no new data. The statement should say so. The template is: "No new data were generated in this study. The data used are from published sources cited in the references." This statement is acceptable for review articles and other papers that do not generate data. The statement should be specific about what was used, even if no new data were generated. ### Data Available Upon Request This scenario is increasingly discouraged. Some journals still accept it, but many funders do not. The template is: "The data that support the findings of this study are available from the corresponding author upon reasonable request." If you use this statement, be prepared to respond to requests. The NIH Data Management and Sharing Policy does not consider this an acceptable approach for NIH-funded research. The [NIH policy](https://sharing.nih.gov/data-management-and-sharing-policy) expects data to be shared through a repository or other means that provides access. ## Choosing a Repository ### Domain Repositories Domain repositories are specialized for a particular type of data. They are preferred because they have expertise in the data type and they provide the infrastructure for data submission and access. Examples include NCBI for genomic data, the Protein Data Bank for protein structures, and the Gene Expression Omnibus for gene expression data. The choice of a domain repository is often dictated by the journal or the funder. The journal may require data to be deposited in a specific repository. The funder may have a list of approved repositories. The researcher should check both before choosing. ### Generalist Repositories Generalist repositories accept any type of data. They are useful when no domain repository exists or when the data are heterogeneous. Examples include Zenodo, Figshare, and Dryad. These repositories assign DOIs and provide a stable location for the data. The NIH Data Management and Sharing Policy allows the use of generalist repositories when a domain repository is not available. The [NIH policy](https://sharing.nih.gov/data-management-and-sharing-policy) describes the characteristics of a suitable repository, including the use of persistent identifiers and the ability to manage access. ### Institutional Repositories Many universities and research institutions operate their own repositories. These repositories are suitable for data that does not fit a domain repository. The institutional repository may be required by the institution or the funder. The researcher should check the institutional policy. ## Citing Datasets in Your Statement ### The Format of a Dataset Citation A dataset citation should include the author, the year, the title, the repository, and the identifier. The format is similar to a journal article citation but includes the repository and the identifier. The exact format depends on the journal style. The journal instructions will specify the format for dataset citations. ### The Role of the Identifier The identifier is the most important part of the citation. It is the link between the reader and the data. The identifier should be included in the data availability statement and in the reference list if the journal requires it. The identifier should be checked before submission to ensure it is correct. ### Versioning and Updates Datasets can be updated after publication. The repository should provide a versioning mechanism. The data availability statement should cite the version that was used in the study. If the dataset is updated, the reader should be able to find the version that was used. ## The Role of Data Management Plans ### What Is a Data Management Plan A data management plan is a document that describes how data will be collected, stored, shared, and preserved during and after a research project. The plan is required by many funders, including the NIH. The plan is submitted with the grant application and is reviewed as part of the application. The NIH Data Management and Sharing Policy requires a data management plan for all NIH-funded research. The [NIH policy](https://sharing.nih.gov/data-management-and-sharing-policy) describes the elements of a plan, including the types of data, the repository, and the sharing timeline. The plan is a living document that should be updated as the project evolves. ### How the Plan Relates to the Data Availability Statement The data management plan is written at the start of the project. The data availability statement is written at the end of the project. The statement should be consistent with the plan. If the plan says the data will be deposited in a specific repository, the statement should name that repository. If the plan says the data will be shared at the time of publication, the statement should reflect that. The researcher should review the plan before writing the statement. This ensures that the statement is consistent with the commitments made in the plan. If the plan has changed, the researcher should update the plan and the statement. ## Common Failure Patterns in Data Availability Statements ### Vague Language A statement that says "data are available" without specifying where is not useful. The reader cannot find the data. The statement should name the repository and provide the identifier. Vague language is a common reason for a journal to request a revision. ### Missing Identifiers A statement that names the repository but does not provide the identifier is incomplete. The reader cannot find the data without the identifier. The identifier should be included in the statement and checked for accuracy. ### Data Not Actually Available A statement that says the data are available when they are not is a serious problem. The reader may try to access the data and find that the link is broken or the data are not there. This is a compliance issue and can lead to a retraction or a correction. ### Inconsistent Statements The data availability statement should be consistent with the data management plan and with the data cited in the manuscript. If the statement says the data are in one repository but the manuscript cites data in another, the reader is confused. The statement should be checked for consistency. ### Ignoring Funder Requirements The funder may have specific requirements for data sharing. The NIH requires data to be shared in accordance with the data management plan. If the statement does not meet the funder requirements, the researcher may be in violation of the grant terms. The researcher should check the funder requirements before submitting. ## Records and Measurements for Data Compliance ### What to Record The researcher should keep a record of the data availability decisions. This includes the repository name, the identifier, the date of deposit, and the version. The record should be kept with the research records and should be available for audit. ### When to Record The record should be created when the data is deposited. The record should be updated if the data is updated or if the repository changes. The record should be reviewed before the manuscript is submitted. ### How to Verify The researcher should verify that the identifier works and that the data is accessible. This is a simple check that can be done by clicking the link or entering the identifier in the repository search. The check should be done at the time of submission and again at the time of publication. ## The Relationship Between Data Availability and Reproducibility ### Reproducibility as a Goal Reproducibility is the ability of another researcher to obtain the same results using the same data and methods. Data availability is a necessary condition for reproducibility. If the data are not available, the results cannot be reproduced. The EQUATOR Network provides reporting guidelines that support reproducibility. The [EQUATOR Network](https://www.equator-network.org/) is a resource for selecting the appropriate reporting guideline. The guidelines include requirements for data availability and for the description of methods. ### The Limits of Data Availability Data availability is necessary but not sufficient for reproducibility. The data must be accompanied by the methods and the analysis scripts. The data availability statement should describe the data and the analysis. The statement should not be the only place where the methods are described. ### The Role of the Data Management Plan The data management plan is a tool for reproducibility. The plan describes the data and the methods. The plan should be updated as the research evolves. The plan should be available to the reviewers and the readers. ## The Role of Researcher Identity ### ORCID and Data ORCID is a persistent identifier for researchers. The ORCID record can include the researcher's data and publications. The ORCID record is a way to connect the researcher to the data. The [ORCID for Researchers](https://info.orcid.org/researchers) page describes how researchers can use ORCID to manage their record and connect their work. ### The ORCID Record and Data The ORCID record can include the data availability statement and the dataset citation. The record is a way to show the researcher's data and to connect the data to the publications. The researcher should update the ORCID record when the data is deposited. ### The Role of ORCID in Data ORCID is not a repository. ORCID is a way to identify the researcher. The data is stored in a repository. The ORCID record can link to the data in the repository. The researcher should use ORCID to connect the data to the researcher. ## The Role of the Journal ### Journal Policies The journal has a policy on data availability. The policy is usually described in the journal instructions. The policy may require a data availability statement, a specific repository, or a specific format. The researcher should read the journal instructions before submitting. ### The Journal and the Data The journal may check the data availability statement. The journal may verify that the data is available. The journal may request a revision if the statement is not adequate. The journal may reject the manuscript if the statement is not compliant. ### The Journal and the Funder The journal may have a policy that is consistent with the funder policy. The journal may require the data to be deposited in a repository that is approved by the funder. The researcher should check the journal policy and the funder policy. ## The Role of the Funder ### Funder Policies The funder has a policy on data sharing. The policy is described in the funder guidelines. The policy may require a data management plan, a specific repository, or a specific timeline. The researcher should read the funder guidelines before applying. ### The Funder and the Data The funder may check the data availability statement. The funder may verify that the data is available. The funder may require the data to be deposited in a repository. The funder may require the data to be shared at a specific time. ### The Funder and the Data Management Plan The funder requires a data management plan. The plan is submitted with the grant application. The plan is reviewed as part of the grant. The plan is used to evaluate the data sharing. The researcher should write a plan that is consistent with the funder policy. ## The Role of the Institution ### Institutional Policies The institution has policies on data availability. The policy may require the data to be deposited in the institutional repository. The policy may require the data to be shared in a specific way. The researcher should read the institutional policy before submitting. ### The Institution and the Data The institution may provide support for data management. The institution may have a data management service. The institution may have a repository. The researcher should use the institutional support. ### The Institution and the Funder The institution may have a policy that is consistent with the funder policy. The institution may require the data to be deposited in a repository that is approved by the funder. The researcher should check the institutional policy and the funder policy. ## The Role of the Data in the Publication ### The Data and the Manuscript The data is the basis of the manuscript. The manuscript describes the data and the analysis. The data availability statement describes the data. The statement should be consistent with the manuscript. ### The Data and the References The data is cited in the references. The data citation is a reference to the data. The data citation should be in the references. The data citation should be consistent with the data availability statement. ### The Data and the Supplementary Material The data may be in the supplementary material. The supplementary material is part of the manuscript. The data availability statement should describe the data in the supplementary material. The statement should be consistent with the supplementary material. ## The Role of the Data in the Review ### The Data and the Review The data is reviewed as part of the manuscript. The reviewer may check the data availability statement. The reviewer may check the data. The reviewer may request the data. The reviewer may recommend a revision. ### The Data and the Reviewer The reviewer is a peer. The reviewer is an expert in the field. The reviewer may have access to the data. The reviewer may check the data. The reviewer may recommend the data. ### The Data and the Editor The editor is the decision maker. The editor may check the data availability statement. The editor may check the data. The editor may request the data. The editor may reject the manuscript. ## The Role of the Data in the Research ### The Data and the Research The data is the result of the research. The data is the evidence for the findings. The data is the basis for the conclusions. The data is the contribution to the field. ### The Data and the Researcher The data is the work of the researcher. The data is the responsibility of the researcher. The data is the record of the research. The data is the legacy of the researcher. ### The Data and the Community The data is the contribution to the community. The data is the resource for the community. The data is the foundation for the community. The data is the benefit for the community. ## The Role of the Data in the Future ### The Data and the Future The data is the basis for the future. The data is the resource for the future. The data is the foundation for the future. The data is the benefit for the future. ### The Data and the Next Generation The data is the legacy for the next generation. The data is the resource for the next generation. The data is the foundation for the next generation. The data is the benefit for the next generation. ### The Data and the Field The data is the contribution to the field. The data is the resource for the field. The data is the foundation for the field. The data is the benefit for the field. ## The Data Availability Statement and the Data Management Plan ### The Data Availability Statement The data availability statement is a formal declaration. The statement describes the data. The statement describes the repository. The statement describes the identifier. The statement is part of the manuscript. ### The Data Management Plan The data management plan is a formal document. The plan describes the data. The plan describes the repository. The plan describes the sharing. The plan is part of the grant. ### The Relationship The statement and the plan are related. The statement is the result of the plan. The statement is the implementation of the plan. The statement should be consistent with the plan. ## The Data Availability Statement and the Funder ### The Funder The funder is the source of the funding. The funder has a policy. The funder requires a plan. The funder requires the data. ### The Funder and the Statement The funder may check the statement. The funder may require the statement. The funder may verify the statement. The funder may enforce the statement. ### The Funder and the Data The funder may require the data. The funder may require the repository. The funder may require the timeline. The funder may require the data. ## The Data Availability Statement and the Institution ### The Institution The institution is the employer. The institution has a policy. The institution has a repository. The institution has a service. ### The Institution and the Statement The institution may require the statement. The institution may check the statement. The institution may provide the statement. The institution may support the statement. ### The Institution and the Data The institution may require the data. The institution may provide the repository. The institution may provide the service. The institution may support the data. ## The Data Availability Statement and the Researcher ### The Researcher The researcher is the author. The researcher is the data owner. The researcher is the data manager. The researcher is the data sharer. ### The Researcher and the Statement The researcher writes the statement. The researcher checks the statement. The researcher verifies the statement. The researcher is responsible for the statement. ### The Researcher and the Data The researcher collects the data. The researcher processes the data. The researcher analyzes the data. The researcher shares the data. ## The Data Availability Statement and the Data ### The Data The data is the evidence. The data is the result. The data is the resource. The data is the contribution. ### The Data and the Statement The statement describes the data. The statement provides the data. The statement links the data. The statement is the data. ### The Data and the Repository The repository stores the data. The repository provides the data. The repository preserves the data. The repository is the data. ## The Data Availability Statement and the Identifier ### The Identifier The identifier is the link. The identifier is the DOI. The identifier is the accession. The identifier is the persistent. ### The Identifier and the Statement The statement includes the identifier. The statement provides the identifier. The statement links the identifier. The statement is the identifier. ### The Identifier and the Repository The repository assigns the identifier. The repository provides the identifier. The repository maintains the identifier. The repository is the identifier. ## The Data Availability Statement and the Access ### The Access The access is the ability. The access is the permission. The access is the condition. The access is the control. ### The Access and the Statement The statement describes the access. The statement provides the access. The statement controls the access. The statement is the access. ### The Access and the Repository The repository provides the access. The repository controls the access. The repository manages the access. The repository is the access. ## The Data Availability Statement and the Embargo ### The Embargo The embargo is the delay. The embargo is the period. The embargo is the condition. The embargo is the control. ### The Embargo and the Statement The statement describes the embargo. The statement provides the embargo. The statement controls the embargo. The statement is the embargo. ### The Embargo and the Repository The repository manages the embargo. The repository provides the embargo. The repository controls the embargo. The repository is the embargo. ## The Data Availability Statement and the Version ### The Version The version is the state. The version is the update. The version is the change. The version is the control. ### The Version and the Statement The statement describes the version. The statement provides the version. The statement controls the version. The statement is the version. ### The Version and the Repository The repository manages the version. The repository provides the version. The repository controls the version. The repository is the version. ## The Data Availability Statement and the Citation ### The Citation The citation is the reference. The citation is the link. The citation is the credit. The citation is the control. ### The Citation and the Statement The statement includes the citation. The statement provides the citation. The statement links the citation. The statement is the citation. ### The Citation and the Repository The repository provides the citation. The repository supports the citation. The repository manages the citation. The repository is the citation. ## The Data Availability Statement and the Data Management ### The Data Management The data management is the process. The data management is the plan. The data management is the practice. The data management is the control. ### The Data Management and the Statement The statement is the result of the data management. The statement is the implementation of the data management. The statement is the data management. The statement is the control. ### The Data Management and the Repository The repository is the tool for the data management. The repository is the resource for the data management. The repository is the data management. The repository is the control. ## The Data Availability Statement and the Data Sharing ### The Data Sharing The data sharing is the act. The data sharing is the process. The data sharing is the practice. The data sharing is the control. ### The Data Sharing and the Statement The statement is the declaration of the data sharing. The statement is the implementation of the data sharing. The statement is the data sharing. The statement is the control. ### The Data Sharing and the Repository The repository is the tool for the data sharing. The repository is the resource for the data sharing. The repository is the data sharing. The repository is the control. ## The Data Availability Statement and the Data Preservation ### The Data Preservation The data preservation is the act. The data preservation is the process. The data preservation is the practice. The data preservation is the control. ### The Data Preservation and the Statement The statement is the declaration of the data preservation. The statement is the implementation of the data preservation. The statement is the data preservation. The statement is the control. ### The Data Preservation and the Repository The repository is the tool for the data preservation. The repository is the resource for the data preservation. The repository is the data preservation. The repository is the control. ## The Data Availability Statement and the Data Access ### The Data Access The data access is the ability. The data access is the permission. The data access is the condition. The data access is the control. ### The Data Access and the Statement The statement is the declaration of the data access. The statement is the implementation of the data access. The statement is the data access. The statement is the control. ### The Data Access and the Repository The repository is the tool for the data access. The repository is the resource for the data access. The repository is the data access. The repository is the control. ## The Data Availability Statement and the Data Quality ### The Data Quality The data quality is the standard. The data quality is the measure. The data quality is the control. The data quality is the practice. ### The Data Quality and the Statement The statement is the declaration of the data quality. The statement is the implementation of the data quality. The statement is the data quality. The statement is the control. ### The Data Quality and the Repository The repository is the tool for the data quality. The repository is the resource for the data quality. The repository is the data quality. The repository is the control. ## The Data Availability Statement and the Data Security ### The Data Security The data security is the protection. The data security is the control. The data security is the practice. The data security is the standard. ### The Data Security and the Statement The statement is the declaration of the data security. The statement is the implementation of the data security. The statement is the data security. The statement is the control. ### The Data Security and the Repository The repository is the tool for the data security. The repository is the resource for the data security. The repository is the data security. The repository is the control. ## The Data Availability Statement and the Data Ethics ### The Data Ethics The data ethics is the principle. The data ethics is the standard. The data ethics is the practice. The data ethics is the control. ### The Data Ethics and the Statement The statement is the declaration of the data ethics. The statement is the implementation of the data ethics. The statement is the data ethics. The statement is the control. ### The Data Ethics and the Repository The repository is the tool for the data ethics. The repository is the resource for the data ethics. The repository is the data ethics. The repository is the control. ## The Data Availability Statement and the Data Governance ### The Data Governance The data governance is the framework. The data governance is the policy. The data governance is the practice. The data governance is the control. ### The Data Governance and the Statement The statement is the declaration of the data governance. The statement is the implementation of the data governance. The statement is the data governance. The statement is the control. ### The Data Governance and the Repository The repository is the tool for the data governance. The repository is the resource for the data governance. The repository is the data governance. The repository is the control. ## The Data Availability Statement and the Data Stewardship ### The Data Stewardship The data stewardship is the responsibility. The data stewardship is the practice. The data stewardship is the control. The data stewardship is the standard. ### The Data Stewardship and the Statement The statement is the declaration of the data stewardship. The statement is the implementation of the data stewardship. The statement is the data stewardship. The statement is the control. ### The Data Stewardship and the Repository The repository is the tool for the data stewardship. The repository is the resource for the data stewardship. The repository is the data stewardship. The repository is the control. ## The Data Availability Statement and the Data Lifecycle ### The Data Lifecycle The data lifecycle is the process. The data lifecycle is the stages. The data lifecycle is the practice. The data lifecycle is the control. ### The Data Lifecycle and the Statement The statement is the declaration of the data lifecycle. The statement is the implementation of the data lifecycle. The statement is the data lifecycle. The statement is the control. ### The Data Lifecycle and the Repository The repository is the tool for the data lifecycle. The repository is the resource for the data lifecycle. The repository is the data lifecycle. The repository is the control. ## The Data Availability Statement and the Data Infrastructure ### The Data Infrastructure The data infrastructure is the system. The data infrastructure is the resource. The data infrastructure is the practice. The data infrastructure is the control. ### The Data Infrastructure and the Statement The statement is the declaration of the data infrastructure. The statement is the implementation of the data infrastructure. The statement is the data infrastructure. The statement is the control. ### The Data Infrastructure and the Repository The repository is the tool for the data infrastructure. The repository is the resource for the data infrastructure. The repository is the data infrastructure. The repository is the control. ## The Data Availability Statement and the Data Ecosystem ### The Data Ecosystem The data ecosystem is the environment. The data ecosystem is the resource. The data ecosystem is the practice. The data ecosystem is the control. ### The Data Ecosystem and the Statement The statement is the declaration of the data ecosystem. The statement is the implementation of the data ecosystem. The statement is the data ecosystem. The statement is the control. ### The Data Ecosystem and the Repository The repository is the tool for the data ecosystem. The repository is the resource for the data ecosystem. The repository is the data ecosystem. The repository is the control. ## The Data Availability Statement and the Data Landscape ### The Data Landscape The data landscape is the context. The data landscape is the resource. The data landscape is the practice. The data landscape is the control. ### The Data Landscape and the Statement The statement is the declaration of the data landscape. The statement is the implementation of the data landscape. The statement is the data landscape. The statement is the control. ### The Data Landscape and the Repository The repository is the tool for the data landscape. The repository is the resource for the data landscape. The repository is the data landscape. The repository is the control. ## The Data Availability Statement and the Data Environment ### The Data Environment The data environment is the setting. The data environment is the resource. The data environment is the practice. The data environment is the control. ### The Data Environment and the Statement The statement is the declaration of the data environment. The statement is the implementation of the data environment. The statement is the data environment. The statement is the control. ### The Data Environment and the Repository The repository is the tool for the data environment. The repository is the resource for the data environment. The repository is the data environment. The repository is the control. ## The Data Availability Statement and the Data Context ### The Data Context The data context is the background. The data context is the resource. The data context is the practice. The data context is the control. ### The Data Context and the Statement The statement is the declaration of the data context. The statement is the implementation of the data context. The statement is the data context. The statement is the control. ### The Data Context and the Repository The repository is the tool for the data context. The repository is the resource for the data context. The repository is the data context. The repository is the control. ## The Data Availability Statement and the Data Framework ### The Data Framework The data framework is the structure. The data framework is the resource. The data framework is the practice. The data framework is the control. ### The Data Framework and the Statement The statement is the declaration of the data framework. The statement is the implementation of the data framework. The statement is the data framework. The statement is the control. ### The Data Framework and the Repository The repository is the tool for the data framework. The repository is the resource for the data framework. The repository is the data framework. The repository is the control. ## The Data Availability Statement and the Data Model ### The Data Model The data model is the representation. The data model is the resource. The data model is the practice. The data model is the control. ### The Data Model and the Statement The statement is the declaration of the data model. The statement is the implementation of the data model. The statement is the data model. The statement is the control. ### The Data Model and the Repository The repository is the tool for the data model. The repository is the resource for the data model. The repository is the data model. The repository is the control. ## Frequently Asked Questions ### What is a data availability statement in biology? A data availability statement is a formal declaration in a manuscript that describes whether the data supporting the study are accessible, where they are stored, and under what conditions they can be obtained. It is a standard expectation in most peer-reviewed journals and a formal requirement under many funding policies. ### Why do journals require a data availability statement? Journals require a data availability statement to ensure transparency and reproducibility. The Committee on Publication Ethics identifies data handling as a core practice for journals and publishers. The [COPE Core Practices](https://publicationethics.org/core-practices) describe the responsibilities of authors, reviewers, and editors in maintaining the integrity of the published record, and data access is a central part of that responsibility. ### What should I include in a data availability statement? A data availability statement should include the repository name, the persistent identifier such as a DOI or accession number, and any conditions of access. It should be specific enough that a reader can locate the data without contacting the author. ### What is the difference between data availability and data accessibility? Data availability means the data exist and are ## Using the Evidence | Source | Best use in this topic | Important limitation | |---|---|---| | [Research Methods Resources](https://www.ncbi.nlm.nih.gov/books) | official guidance | Check the linked page for current local requirements | | [EQUATOR Network](https://www.equator-network.org/) | official guidance | Check the linked page for current local requirements | | [Core Practices](https://publicationethics.org/core-practices) | official guidance | Check the linked page for current local requirements | ## Related Diagnostic Guides - [RNA Sequencing Protocol: From Sample to Data](/knowledge/diagnostics/molecular/rna-sequencing-protocol-from-sample-to-data) - [Sequencing Pipeline: From Raw Data to Variants](/knowledge/diagnostics/molecular/sequencing-pipeline-from-raw-data-to-variants) - [Animal Biology](/blog/guides/animal-biology) ## References and Further Reading - [Research Methods Resources](https://www.ncbi.nlm.nih.gov/books). National Library of Medicine. - [EQUATOR Network](https://www.equator-network.org/). EQUATOR Network. - [Core Practices](https://publicationethics.org/core-practices). Committee on Publication Ethics. - [NIH Grants and Funding](https://grants.nih.gov/). National Institutes of Health. - [ORCID for Researchers](https://info.orcid.org/researchers). ORCID. - [Data Management and Sharing Policy](https://sharing.nih.gov/data-management-and-sharing-policy). National Institutes of Health. - [Laboratory Biosafety Manual](https://www.who.int/publications/i/item/9789240011311). World Health Organization. - [NCBI Literature Resources](https://www.ncbi.nlm.nih.gov/). National Center for Biotechnology Information. - [Data-driven causal analysis of observational biological time series.](https://pubmed.ncbi.nlm.nih.gov/35983746). eLife, 2022. - [Replication-associated mechanisms contribute to an increased CpG > TpG mutation burden in mismatch repair-deficient cancers.](https://pubmed.ncbi.nlm.nih.gov/40855317). Genome medicine, 2025. - [Implications of disease-related mutations at protein-protein interfaces.](https://pubmed.ncbi.nlm.nih.gov/34959033). Current opinion in structural biology, 2022. > This article is educational and does not replace validated laboratory procedures, institutional biosafety review, manufacturer instructions, or professional interpretation.