Open data policy

M@n@gement strongly encourages authors to make all data associated with their submission openly available, whenever possible and under the necessary access conditions, according to the FAIR principles (Findable, Accessible, Interoperable, Reusable) and CARE principles for Indigenous Data Governance (Collective benefit, Authority to Control, Responsibility, Ethics).

Definition of Research Data and exceptions

This policy applies to research data that would be necessary to check the results presented in the publications of the journal. Research data include data produced by the authors as well as data from other sources that are analyzed by the authors in their study. These data can be presented in various forms: images, videos, texts, codes, statistical tables. . .

These data must be produced and shared in compliance with FAIR and CARE principles (

Research data that are not necessary to check the results reported in publications are not covered by this policy.

This policy will be limited by the legitimate exceptions regulated by law, for example with regard to professional confidentiality, industrial and commercial secrets, personal data or content protected by copyright.

M@n@gement does not review and publish data papers. But we encourage authors to add data papers to their datasets as presentations in order to clarify data procedures, conditions and limits or reuses.

Data and metadata standards and formats

The journal encourages authors to use open and standard formats.

Descriptive metadata must be structured using recognized standards, at least Dublin Core. Standards used by researchers can be either disciplinary or more generic (

The use of “controlled” (or reference) vocabularies, either disciplinary or more generic ones, to express these metadata is recommended (e.g., to reference an author, see:; to reference a place, see:, or for data concepts see Controlled Vocabularies for Repositories). Compliance of data file formats with CINES recommendations for long-term preservation is also recommended (, in French).

Data access and hosting

The data that contributed to the writing of the publication must be deposited in a data repository that will guarantee secure storage and access to the data, in particular through the attribution of a permanent identifier.

We advise authors to avoid the use of private repositories whose roadmap is not transparent in terms of economic model, governance, sustainability . . . (e.g., Figshare).

The journal recommends data be deposited in a repository, whether it is generalist (e.g., Zenodo), institutional (e.g., Data INRAE) or disciplinary (e.g., beQuali for qualitative survey data, or Nakala for Social Sciences and Humanities).

In all cases, authors should check that the chosen repository meets the following main quality criteria: see (in French).

We invite authors to contact their institution’s support services as regards good practices of data management and sharing, and the design and development of data management plans.

Data availability procedures

Submission phase

Authors are not encouraged to transmit the data when submitting their contributions whenever possible. This can be done either within the article, in appendix (dataset option on our platform) but preferably through a restricted or controlled access via a repository. It remains necessary that data are anonymized and follow general recommendations. This includes the anonymization of the research project itself, principal investigator and research participants. This includes the anonymization of the research project itself, principal investigator and research participants.

Peer reviewing phase

If editors and reviewers deem it necessary, the authors should make the data that support the results reported in their contribution available for reviewers. Refusal to provide data when asked will result in the paper being declined.

Acceptance phase

When it is possible, data should be made available without embargo, or with the shortest embargo period possible when the paper is accepted. Sharing terms must allow reuse, with an explicit link between the data and the publication they support, under normal conditions (in compliance of personal data guidance and protection of interviewees).

The journal encourages authors to share data under open licenses that allow for their free reuse. Authors must use the licenses recommended by the repository where the datasets were deposited.

By publishing in this journal, authors commit to make the data and metadata publicly available for at least 5 years after their contribution has been published, either through a platform, or by individual provision if the data cannot be freely shared.

Alternatives to open access sharing of personal or sensitive data are:

  • Anonymization or pseudonymization of the data before open access release
  • Data available on request for research purposes only
  • Availability of the metadata of data only, which should be the minimal objective for all authors in M@n@gement.

Data accessibility statement

Authors are expected to cite the datasets underlying their publications in a specific data accessibility statement. This section must describe the available data, how to access them, and provide a permanent link to the data.

The statement may include one, or a combination, of the following:

  • The datasets generated during and/or analyzed during the current study are available in the [NAME] repository; [DOI].
  • The datasets generated during and/or analyzed during the current study are not available in open access due, in which case the reason needs to be specified, but are available from the author on reasonable request.
  • Data sharing does not apply to this article because no datasets were generated or analyzed during the current study.
  • The datasets on which the current study is based were not generated by the authors. They are available online: Creator (Year of publication). Title. Version. [Repository Name]. [DOI]