Data Management and Sharing Policy

The Revista Aurora, in alignment with Open Science processes, encourages the sharing of research data—including data, program codes, and other underlying materials of the manuscript. This sharing should be done in a manner that respects participant privacy and addresses other pertinent ethical issues.

Why Share Data?

Data are a fundamental outcome of research activities, contributing to the preservation and reuse of materials and information in new research endeavors.

Funding agencies worldwide have begun to require data sharing as one of the criteria for research funding. This movement toward data sharing is also gaining traction across various fields of knowledge, ensuring transparency, reliability, and reproducibility.

For sharing, authors may use their institutional repositories, as well as identify relevant and certified repositories. The Revista Aurora recommends some repositories that may be used:

  • Search for relevant Ibict and GovBR repositories;
  • Dryad; • Figshare; • Harvard Dataverse;
  • Inter-university Consortium for Political and Social Research (ICPSR);
  • Open Science Framework (OSF);
  • Science Data Bank (SDB);
  • The Qualitative Data Repository;
  • UK Data Service;

The Data Management Plan (DMP) describes the data collected or generated; the methodologies and standards used in these processes; whether, how, and under what conditions these data are shared and/or made open to the scientific community; and how they are curated and preserved.

The DMP should include:

  1. Description of the data and metadata produced by the project: samples, collection records, forms, models, experimental results, software, graphs, maps, videos, spreadsheets, audio recordings, databases, educational material, and others.
  2. When applicable, legal or ethical restrictions for sharing such data, policies to ensure privacy, confidentiality, security, intellectual property, and others.
  3. Preservation and sharing policy (immediate sharing or only after acceptance of the associated publication); embargo period (before sharing) and the period during which the data will be preserved and made available.
  4. Description of mechanisms, formats, and standards for storing such items to make them accessible to third parties. This description may include the use of repositories and services from other institutions (FAPESP, 2021).

It is recognized that there may not always be specific research data, or it may not be possible to share them publicly. In such cases, the author has the following options when submitting (the statement should be provided as a separate section titled ‘Data Availability’ at the end of the main text, before the References section):

  • The data generated during this research are available at [REPOSITORY NAME], [PERSISTENT INTERNET LINK TO DATASETS].
  • The data generated during this research are available from the corresponding author upon request.
  • The data generated and/or analyzed during this research are included in the published text (or in Supplementary Information).
  • The data generated during this research are not publicly available due to [REASON], but are with the corresponding author, who may consider sharing them with interested parties.
  • No datasets were generated or analyzed during the current study.

The repository where the data and information are located, if applicable, should be cited in the text according to the Research Data Citation Guide, preferably in the methodology section, included in the reference list, and in the “Research Data Availability” section.

References

FAPESP. Diretrizes para Planos de Gestão de Dados (PGD) para propostas de centros. São Paulo, 2021. Disponível em: https://fapesp.br/14974/diretrizes-para-planos-de-gestao-de-dados-pgd-para-propostas-de-centros. Acesso em: 28 Ago. 2024.

SciELO. Guia de citação de dados de pesquisa [online]. SciELO, 2018 Disponível em: https://wp.scielo.org/wp-content/uploads/guia-de-citacao-de-dados_pt.pdf. Acesso em: 28 Ago. 2024.