PREreview estructurada del Reuso de dados de pesquisa em acesso aberto no SciELO Data: uma análise exploratória por meio das citações
- Publicado
- DOI
- 10.5281/zenodo.17970313
- Licencia
- CC BY 4.0
- Does the introduction explain the objective of the research presented in the preprint?
- Yes
- Are the methods well-suited for this research?
- Neither appropriate nor inappropriate
- Citation Analysis: Relying solely on DataCite via Crossref may miss citations from non-DOI sources (e.g., Google Scholar, Dimensions, or manual citations in gray literature). The authors note Make Data Count showed zero metrics, but they should explore why (e.g., integration issues in SciELO Data) and consider alternative tools like OpenCitations or PlumX for triangulation. Download Metrics: Summing individual file downloads (2,112 total) is a workaround, but it overestimates unique accesses if users download multiple files per session.
- Are the conclusions supported by the data?
- Somewhat supported
- Are the data presentations, including visualizations, well-suited to represent the data?
- Somewhat appropriate and clear
- How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?
- Somewhat clearly
- Is the preprint likely to advance academic knowledge?
- Moderately likely
- Increase the sample if feasible (e.g., all datasets from the 22 journals) or justify the current size statistically. Incorporate correlation analyses (e.g., between file format and downloads) using the collected metadata. Enhance Discussion: Address counterarguments, such as why self-citation might not indicate "true" reuse (per Park & Wolfram). Propose concrete policy recommendations, like integrating data deposits into CAPES/CNPq evaluations. Supplementary Materials: Provide the Python script, Excel data, and a full list of the 75 datasets/DOIs as supplements for reproducibility.
- Would it benefit from language editing?
- Yes
- Would you recommend this preprint to others?
- Yes, but it needs to be improved
- this manuscript has strong potential to contribute to open science literature but needs substantial revisions to address methodological limitations, improve clarity, and deepen analysis. With these changes, it would be suitable for publication in a journal like Data Science Journal or Encontros Bibli
- Is it ready for attention from an editor, publisher or broader audience?
- No, it needs a major revision
Competing interests
The authors declare that they have no competing interests.
Use of Artificial Intelligence (AI)
The authors declare that they did not use generative AI to come up with new ideas for their review.