Editorial Policies
- COPE Recommendation for Plagiarism
- COPE Recommendation for Conflict of Interest (specific to editors)
- Editorial Process
- Creative Commons License
- Publication Ethics and Malpractice Statement
- Conflict of Interest and Financial Disclosures (specific to editors)
- Publisher Policies
- Advertisement Policies
- Editorial Policies
- Peer Review Process
1. COPE Recommendation for Plagiarism
In accordance with the Committee on Publication Ethics (COPE) guidelines, the *Data Science Journal* has a strict policy against plagiarism. All submitted manuscripts are screened for plagiarism using specialized software to ensure the originality of the work. If plagiarism is detected—whether it be from published sources, other research, or unpublished works—the manuscript will be rejected, and the authors will be notified about the breach of ethical standards. In cases of severe plagiarism, the *Data Science Journal* reserves the right to take further actions, such as notifying the authors' institutions or retracting previously published articles.
2. COPE Recommendation for Conflict of Interest (specific to editors)
Editors of the *Data Science Journal* are required to disclose any potential conflicts of interest, which could influence their editorial decisions. These conflicts may arise from financial ties, academic collaborations, or personal relationships with authors or institutions involved in the submitted manuscript. To ensure transparency and maintain the integrity of the review process, editors must recuse themselves from handling manuscripts where such conflicts exist. Any relevant disclosures will be made publicly available, and the editorial board will assess whether a conflict of interest compromises the review process or the journal’s impartiality.
3. Editorial Process
The editorial process of the *Data Science Journal* follows a multi-step procedure designed to ensure quality and transparency in the publication of research. After submission, the manuscript is first screened for compliance with the journal's scope and ethical guidelines. If the manuscript passes this initial review, it is sent to two or more peer reviewers with expertise in the relevant area. Reviewers evaluate the quality, originality, methodology, and significance of the research. Authors are then asked to revise the manuscript based on reviewer feedback. After revisions, the manuscript is re-evaluated before a final decision is made by the editor. Authors are informed of the decision, which may involve acceptance, further revision, or rejection. Throughout this process, the journal adheres to strict timelines and ensures clear communication with authors.
4. Creative Commons License
All articles published in the *Data Science Journal* are made freely available under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This license allows others to share, copy, and adapt the work, provided they credit the original authors and the journal, and do not use the work for commercial purposes. The Creative Commons license promotes openness and accessibility, allowing the research published in the journal to have a broader impact while protecting the intellectual property rights of authors.
5. Publication Ethics and Malpractice Statement
The *Data Science Journal* is committed to upholding the highest ethical standards in publishing. We follow the principles outlined by COPE and other international bodies to prevent and address issues of research misconduct. The journal promotes transparency, reproducibility, and integrity in data science research. Any act of research misconduct, such as falsification, fabrication, plagiarism, or duplicate publication, is grounds for rejection of a manuscript or retraction of a published article. In cases of suspected ethical violations, the journal follows a rigorous investigation process and takes appropriate actions based on COPE guidelines. Authors, reviewers, and editors are expected to maintain the highest standards of honesty and responsibility.
6. Conflict of Interest and Financial Disclosures (specific to editors)
Editors are required to disclose any financial or non-financial conflicts of interest that could influence their editorial decisions. This includes personal, professional, or financial relationships with authors, institutions, or organizations that could be seen as affecting their objectivity. If an editor has a potential conflict of interest, they must recuse themselves from handling that particular manuscript. All financial disclosures and potential conflicts of interest are made available to ensure transparency in the editorial process. These policies help maintain the integrity of the review process and prevent bias in decision-making.
7. Publisher Policies
The *Data Science Journal* adheres to publishing practices that align with the standards of reputable academic publishing organizations. The publisher ensures the timely and professional dissemination of research, adhering to transparency, accountability, and ethical standards in all areas of editorial and publication processes. The publisher supports the journal’s commitment to open access, rigorous peer review, and ethical integrity. All published articles are made freely accessible to readers, ensuring that knowledge in data science can be shared globally.
8. Advertisement Policies
The *Data Science Journal* accepts advertisements, but these are clearly distinguishable from editorial content. Advertisements are relevant to the data science field and must not interfere with the editorial integrity or peer review process. The journal ensures that advertisements do not influence the content or decisions regarding published research. Any commercial or promotional content is reviewed to comply with ethical guidelines and is marked as sponsored or paid content.
9. Editorial Policies
The *Data Science Journal* maintains editorial policies that promote rigorous academic standards, transparency, and objectivity in the publishing process. The journal publishes original research articles, reviews, and technical papers that contribute to the development of data science. All manuscripts must adhere to the journal's scope, guidelines, and ethical standards. The editorial board ensures that decisions are made based on the quality and significance of the research, with the primary aim of advancing the field of data science. These policies include procedures for handling potential conflicts of interest, ensuring the integrity of the peer review process, and promoting the responsible reporting of research findings.
10. Peer Review Process
The *Data Science Journal* follows a double-blind peer review process, where both authors and reviewers remain anonymous throughout the review stage. Upon submission, manuscripts are first assessed by the editor to ensure they align with the journal’s scope and ethical standards. If accepted for peer review, the manuscript is sent to independent experts who evaluate the work for scientific rigor, innovation, clarity, and relevance to the field of data science. Reviewers provide detailed feedback, which is used to guide revisions and improve the quality of the manuscript. Authors are given the opportunity to revise their work in response to reviewer comments, and the revised manuscript undergoes further evaluation. The journal strives to ensure that the peer review process is fair, unbiased, and constructive. Only manuscripts that meet high academic standards are published, ensuring that the journal remains a trusted source of high-quality research in the data science community.
