Submissions
Submission Preparation Checklist
As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines.- Originality: The contribution is original and has not been previously published, and it is not under consideration by another journal. If there is any relevant overlap (e.g., a preprint, technical report, earlier version, or related submission), this must be disclosed and justified in “Comments to the Editor.”
- File format: The submission file is in Microsoft Word, OpenOffice, or RTF format.
- URLs/DOIs in references: Where available, URLs/DOIs have been provided for the references.
- Minimum formatting: The manuscript is formatted with 1.5 line spacing, uses 12-point font, uses italics rather than underlining (except for URLs), and includes figures and tables embedded in the text (not placed at the end as attachments).
- Compliance with Author Guidelines: The manuscript follows the style standards and bibliographic requirements described in the Author Guidelines on the About the Journal page, including use of the official template.
- Manuscript type and LADS scope: The submission has been correctly categorized as a Data Paper or a Research Article, and it fits the LADS scope (data-driven scholarship).
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Ethics, integrity, and Brazil’s LGPD: The corresponding author, on behalf of all co-authors (when applicable), declares that the research and the collection/use of data were conducted ethically and in compliance with applicable regulations—especially when involving human participants, animals, and/or personal data.
When personal data are involved (including data obtained from interviews, surveys/forms, social networks, and/or any information that can identify individuals directly or indirectly), authors declare compliance with Brazil’s General Data Protection Law (LGPD – Law No. 13,709/2018) and that appropriate anonymization/de-identification measures were applied, including risk minimization of re-identification, as applicable.
Authors also declare that they are the data owners and/or have full authorization and a lawful basis to share the data for scholarly publishing purposes, and that there are no contractual restrictions (confidentiality, non-disclosure agreements, exclusive rights, or similar) that prevent dataset availability under LADS policies. - Mandatory data (all submissions): The associated dataset has been submitted together with the manuscript (as supplementary files) and/or is already available in a recognized repository, with an access link/identifier provided. The dataset must be robust, preferably based primarily on primary data and/or with a clear scientific contribution in curation/organization/methodology that supports its value and reuse potential.
- Minimum dataset documentation: The dataset is sufficiently documented to enable reuse, including (when applicable) a README and a data dictionary/codebook (variables, units, codes/categories, and missing values). If scripts/code were used for cleaning, transformation, or analysis, authors are encouraged to provide them to support reproducibility.
- Complete author metadata in the system (required): The corresponding author will register all authors in the system, providing: First and last name; contact email; country; ORCID; affiliation. This information must be entered during submission in the system fields. It is not sufficient for these details to appear only in the manuscript; they must be added individually in the submission metadata.
- Dataset license and citation: The dataset must include an explicit reuse license (e.g., Creative Commons). When a DOI/persistent identifier exists, include a formal dataset citation in the manuscript references (or in the indicated “How to cite” field).
Data papers
This section exclusively publishes articles in data paper format, which present a robust dataset, predominantly of primary data and with scientific methods that enable its use in scientific production.
Articles should be submitted via the official LADS website and should be structured using the template provided by the journal, preferably containing between 5 and 10 pages.
Research Articles
This section publishes Research Articles reporting scientific objectives, methods, results, and discussion, provided that each manuscript is accompanied by a robust dataset, properly documented and made openly available (as supplementary files within the system and/or deposited in a recognized open repository), enabling reproducibility, transparency, and reuse.
At minimum, the dataset must include reuse-enabling documentation (e.g., a README and a data dictionary/codebook defining variables, units, codes/categories, and missing values). When applicable, authors are encouraged to provide the scripts/code used for data processing and analysis.
Manuscripts must be submitted through the official LADS website and prepared using the journal template. A recommended length is 8–15 pages (or 3,000–6,000 words, as applicable), unless otherwise justified.
Note on ethical/legal restrictions
When data cannot be fully shared due to ethical or legal constraints (e.g., personal/sensitive data), authors must provide a justification and an appropriate sharing alternative (e.g., de-identified data, aggregated data, synthetic data, or controlled access when strictly necessary).
Copyright Notice
The submission of manuscripts to LADS implies the transfer by the authors of the publication rights. The copyright for articles published in this journal belongs to the author, with the journal's rights over the first publication. Authors may only use the same results in other publications by clearly indicating LADS as the medium of the original publication.
Articles published in LADS are licensed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium provided the original publication is properly cited.
Privacy Statement
The names, email addresses, and any other personal information entered on this journal website will be used exclusively for the journal’s stated purposes (e.g., user registration, submissions, peer review, editorial communication, publication, and related indexing services) and will not be made available for any other purpose or to any other party.
Data that help improve the publishing platform may be shared with the platform developer (Public Knowledge Project – PKP) in an anonymized and aggregated form, with appropriate exceptions such as article metrics. The data will not be sold by the journal or PKP and will not be used for purposes other than those stated here.
If we use embedded third-party forms (e.g., Google Forms) for specific workflows, information submitted through those forms is also subject to the provider’s applicable policies.
You may request access, correction, updating, anonymization, portability, or deletion of your personal data, in accordance with Brazil’s LGPD (Law No. 13,709/2018), by emailing: contact@datainscience.com.br