Author Policies
1. English Language Editing
2. Sample Paper
3. Errata, Retractions, and Corrigenda Policy
4. APC Waiver Policy
5. Human and Animal Rights Policy
6. Open Access Policy
7. Data Sharing Policy
8. Article Processing Charge
9. Participant/Patient Privacy and Informed Consent
10. Rights and Grants to the Author
11. Copyright Policy
12. Check List
13. Digital Preservation
14. Manuscript Preparation
15. Licensing Policy
16. Submission of Manuscript
17. Complaints Policy
18. Plagiarism Policy
19. Author’s Agreement Form
20. Withdrawal Policy
1. English Language Editing
In academic publishing, the clarity and readability of a manuscript are essential to ensure that the research is accessible to a global audience. The **English Language Editing** policy outlines that authors whose first language is not English may be required to have their manuscript edited for grammar, syntax, and readability. This service is often provided by professional editing services that specialize in academic writing. Authors are strongly encouraged to seek professional editing before submission to improve their chances of acceptance. This is particularly important in fields like data science, where complex technical language can be difficult to understand. The journal may either offer a list of recommended editing services or partner with an external provider. Authors should also ensure that the content adheres to the journal's style guidelines, ensuring consistency across the publication. The language editing is not a substitute for peer review but an additional step to ensure that the quality of communication is up to standard for an international readership. While some journals offer language editing as a free service or at a discounted rate, others may charge authors directly for this service.
---
2. Sample Paper
A Sample Paper provides authors with an example of how to structure and format their manuscript according to the journal’s guidelines. For a data science journal, the sample paper typically demonstrates the correct format for sections like the abstract, introduction, methods, results, discussions, and conclusion. Additionally, it will illustrate how to format references, tables, figures, and equations correctly. Sample papers are invaluable tools for authors as they give clear examples of acceptable formatting and structure, reducing the likelihood of errors in submission. For data science manuscripts, particular attention is given to presenting algorithms, code snippets, and datasets clearly, as these elements are essential to reproducibility and transparency in the field. The sample paper will also highlight common style choices such as font size, margins, and citation styles. Authors are encouraged to refer to the sample paper when preparing their manuscripts to ensure that they comply with the journal’s formatting requirements. Adherence to these guidelines helps the editorial team process manuscripts more efficiently and improves the chances of successful publication.
3. Errata, Retractions, and Corrigenda Policy
The Errata, Retractions, and Corrigenda Policy is a vital aspect of academic publishing as it maintains the integrity of the journal's published content. An erratum is a correction of a published article due to errors that do not significantly affect the article’s findings, such as typographical errors or minor mistakes in formatting. A corrigendum refers to a correction of a more substantial nature that requires updating or clarifying specific details in the published work. A retraction, on the other hand, occurs when serious issues are found in the article that fundamentally undermine its findings or methodology, such as issues with data integrity, ethical violations, or unintentional duplication of results. In data science journals, retractions may also be necessary when the data used in the study is proven to be inaccurate or misleading. The policy outlines the procedures for addressing such issues, including the responsibilities of authors, editors, and the publisher in ensuring corrections are made transparently. Retractions and corrections are typically published in the same journal issue or in an addendum, and they are also included in citation databases to ensure proper academic and research records.
4. APC Waiver Policy
The APC Waiver Policy outlines the conditions under which an author may be exempt from paying the Article Processing Charge (APC). The APC is a fee that covers the costs of publishing an article in an open-access journal, which includes peer review, editing, formatting, and hosting. However, some authors, particularly those from institutions or countries with limited research funding, may be unable to afford this fee. The APC Waiver Policy ensures that these authors still have the opportunity to publish their work in an open-access format, making their research freely available to the global community. Typically, waivers are granted based on factors such as geographic location, institutional funding, or the author's financial status. The policy may include a clear procedure for applying for an APC waiver, with the author required to provide supporting documentation or justification. The policy ensures equitable access to the journal’s publication opportunities and promotes inclusivity in the dissemination of scientific research, especially in fields like data science, where research collaborations are often global.
5. Human and Animal Rights Policy
The Human and Animal Rights Policy ensures that all research published in the journal adheres to ethical standards when dealing with human and animal subjects. In data science, this often involves research that utilizes real-world data from human participants or animal experiments. Authors must adhere to recognized ethical guidelines, including the Declaration of Helsinki for human studies and the Animal Research: Reporting In Vivo Experiments (ARRIVE) guidelines for animal research. The policy stipulates that authors must obtain informed consent from participants and ensure that privacy and confidentiality are respected. It also mandates the appropriate ethical review and approval by relevant institutional review boards or ethics committees before research can be conducted. The journal reserves the right to reject any manuscript that fails to comply with these ethical standards. The goal is to ensure that all research, particularly in sensitive fields like data science, which often involves large datasets with personal or health-related information, is conducted responsibly and ethically, with the well-being of participants and animals prioritized.
6. Open Access Policy
The Open Access Policy of a journal ensures that all published content is freely available to readers without subscription or paywall barriers. Open access allows the wider scientific community, policymakers, and the general public to access cutting-edge research without cost. For data science, this is especially crucial, as it ensures that valuable research findings, algorithms, and datasets are accessible to practitioners, researchers, and students across the globe. Authors usually retain copyright of their work but provide the journal with a license to publish under open access terms. The policy may specify the type of open access, such as Green Open Access (where authors deposit their preprints in institutional repositories) or Gold Open Access (where articles are made immediately available upon publication). Open access publishing facilitates the dissemination of knowledge and promotes reproducibility, a key principle in data science. The policy may also mention options for hybrid open access, where authors can choose to pay APCs for specific articles to be open access, while the rest of the content remains behind a paywall.
7. Data Sharing Policy
The Data Sharing Policy mandates that authors make their data publicly available to ensure the transparency and reproducibility of research findings. In data science, where research often involves large datasets or proprietary algorithms, data sharing is critical to allow other researchers to verify results, replicate studies, and build upon existing work. Authors are typically required to upload datasets to publicly accessible repositories (such as GitHub, Zenodo, or Figshare), providing proper documentation on how the data was collected, cleaned, and processed. The policy outlines the types of data that must be shared (e.g., raw data, processed data, model outputs) and any exceptions, such as cases where data sharing could violate privacy agreements or confidentiality agreements. The policy encourages authors to follow best practices for data management and sharing, including adhering to FAIR principles (Findability, Accessibility, Interoperability, and Reusability). By promoting open data, the journal fosters an environment of collaboration and transparency, which is especially important in fields like data science, where reproducibility and validation of results are key.
8. Article Processing Charge (APC)
The Article Processing Charge (APC) is a fee required to publish an article in an open-access journal. APCs cover the costs of the editorial and publishing processes, including peer review, copyediting, formatting, and online hosting. In data science journals, APCs may also cover the costs of data sharing, digital preservation, and ensuring the accessibility of supplementary materials like code or datasets. The fee structure is typically outlined in the journal’s submission guidelines, and the amount may vary depending on the journal’s prestige or impact factor. Some journals may offer discounts or waivers based on an author's financial situation or geographic location. The policy provides transparency about these charges and may outline specific payment options for authors. The APC model ensures that research remains freely accessible while maintaining the journal’s financial sustainability. Journals that employ this model are typically committed to disseminating research as widely as possible, contributing to the open science movement. Authors should review this policy carefully to understand their financial obligations before submitting a manuscript.
9. Participant/Patient Privacy and Informed Consent
The Participant/Patient Privacy and Informed Consent Policy is crucial for maintaining ethical standards in research, particularly in studies involving sensitive data. In the field of data science, this often applies to research involving personal, medical, or demographic information. Authors must ensure that they have obtained informed consent from all human participants, meaning that participants are fully aware of the research purpose, the types of data being collected, and how it will be used. In addition, authors must guarantee that participant confidentiality is upheld, and that data is anonymized or de-identified whenever possible. If the research involves patient data, the policy may reference additional protections, such as compliance with privacy laws like HIPAA in the United States or GDPR in Europe. The journal will typically require authors to declare that all ethical guidelines have been followed, and any data used in the study complies with relevant privacy regulations. This policy safeguards the privacy and rights of individuals involved in research, ensuring that their participation does not result in harm or breaches of confidentiality.
10. Rights and Grants to the Author
The Rights and Grants to the Author policy clarifies the rights authors retain after their work is published in the journal. In most cases, authors retain copyright to their work but grant the publisher a license
to publish and distribute the article under specified conditions. In the case of an open-access journal, this license is often non-exclusive, allowing authors to retain full rights to share and reuse their work in other formats, such as in presentations, books, or as part of future studies. The policy may outline whether authors can deposit their manuscripts in institutional repositories or share them with colleagues before publication. It also clarifies that the journal has the right to reproduce the article for the purpose of distribution, marketing, and archival purposes. For data science research, this policy is particularly important for authors who wish to share their work openly in the academic community while maintaining control over intellectual property, particularly when datasets or algorithms are involved. The policy fosters a fair balance between author rights and the publisher’s need to disseminate research widely.
11. Copyright Policy
The Copyright Policy outlines the ownership of intellectual property rights concerning the publication of articles in the journal. Typically, copyright is held by the author, but the author grants the publisher a license to publish, distribute, and publicly display the article. This policy is crucial to clarify how authors can use their own work post-publication and under what circumstances the journal can reuse the content. In an open-access journal, authors may retain copyright but agree to allow the article to be freely distributed under specific licenses, such as Creative Commons licenses. The policy ensures that authors can still share and reuse their work, while also protecting the publisher’s right to manage the publication process. For data science research, the policy may also address the ownership of datasets, algorithms, and supplementary materials. The copyright policy may allow authors to retain ownership of datasets and software they create, with the journal simply providing a platform for sharing and dissemination. It is essential for authors to understand the terms outlined in the copyright policy to protect their intellectual property.
12. Check List
A Check List is a list of items or requirements that authors must verify before submitting their manuscript to the journal. This ensures that all necessary components are included and that the manuscript adheres to the journal’s guidelines. For a data science journal, the checklist may cover the following aspects: proper formatting, adherence to word count limits, inclusion of an abstract, keywords, and appropriate referencing styles. It may also include requirements for submitting data and code, ethical statements, and conflicts of interest. By providing authors with a clear and detailed checklist, the journal helps streamline the submission process, reduces the chances of errors or omissions, and improves the overall quality of submitted manuscripts. The checklist serves as a practical tool for authors to ensure that their manuscript is fully prepared and ready for review, helping to prevent delays in the editorial process.
13. Digital Preservation
The Digital Preservation policy ensures that all articles published in the journal are archived and preserved for long-term access. This is essential in ensuring that scholarly research remains accessible, even as technologies change. For a data science journal, this includes preserving datasets, code, and supplementary materials that may accompany published articles. The journal may partner with digital preservation repositories or services, such as CLOCKSS or Portico, to ensure that its content remains accessible long after initial publication. The policy outlines the procedures for preserving both the journal’s content and associated data, with an emphasis on ensuring that materials are retrievable and readable even as file formats or platforms evolve. This is especially important for fields like data science, where datasets and algorithms are central to the research. Preserving digital content also supports academic transparency, reproducibility, and the continued usefulness of the published research.
14. Manuscript Preparation
The Manuscript Preparation policy provides detailed guidelines on how authors should format and prepare their manuscripts for submission. This typically includes requirements for the structure of the manuscript, including sections like the title page, abstract, introduction, methodology, results, discussion, conclusion, and references. For data science manuscripts, additional sections might be required for describing datasets, algorithms, and statistical analyses. Authors may also need to follow specific formatting for equations, figures, and tables, especially if the work includes technical models or software code. The policy may specify formatting details such as font type, font size, line spacing, margin width, and citation style. By following these guidelines, authors can ensure that their manuscript is easily processed by the editorial team, which helps speed up the peer review and publication process.
15. Licensing Policy
The Licensing Policy defines how authors can license their work upon acceptance for publication. It typically includes options for authors to choose a specific license, such as Creative Commons licenses, which allow others to reuse, remix, and redistribute the work under specified conditions. For data science research, this policy ensures that authors retain control over the dissemination of their intellectual property while making their work available to the scientific community. Authors may also have the option to select a restrictive license, depending on the sensitivity of the data involved in the research. The licensing policy ensures clarity and transparency about how the work can be used post-publication, promoting ethical and legal compliance in data sharing.
16. Submission of Manuscript
The Submission of Manuscript policy outlines the process by which authors submit their work to the journal for consideration. This typically involves online submission platforms, where authors must upload their manuscript, supporting documents (such as a cover letter, data availability statements, and conflict of interest disclosures), and any supplementary materials. The policy also outlines the submission deadlines, any formatting requirements, and the steps authors must take to submit their manuscript, including signing necessary agreements.
17. Complaints Policy
The Complaints Policy ensures that there is a clear and transparent process for addressing concerns raised by authors, reviewers, or readers. This may involve complaints about the editorial process, decisions made during peer review, or ethical concerns regarding the published work. The policy provides a step-by-step guide for submitting a formal complaint, which is typically handled by a designated committee or the journal’s editorial board. The aim is to ensure fairness, transparency, and the timely resolution of disputes.
18. Plagiarism Policy
The Plagiarism Policy outlines the measures the journal takes to prevent plagiarism and academic misconduct. This includes using plagiarism detection tools to assess the originality of submitted manuscripts. The policy may describe the journal’s commitment to ethical publication practices and the consequences for authors who submit plagiarized work, which could include rejection or retraction of the article.
19. Author’s Agreement Form
The Author’s Agreement Form is a contract between the author and the journal that details the rights and responsibilities of both parties. This agreement typically covers issues such as copyright ownership, the author's commitment to the accuracy of the work, and any financial obligations such as APCs.
20. Withdrawal Policy
The Withdrawal Policy outlines the circumstances under which an author can withdraw their manuscript from the review or publication process. It typically includes steps for formal withdrawal, potential consequences for late withdrawal, and situations where the manuscript may be retracted after publication.
