Peer Review Policy

The International Journal of Data Sciences and Intelligent Systems (IJDSS) maintains a rigorous and transparent peer review process to ensure the publication of high-quality, original, and impactful research. All submitted manuscripts undergo double-blind peer review, where both the reviewers and authors remain anonymous, to eliminate bias and maintain objectivity in the evaluation process.

Key Features of the Peer Review Process:

  1. Initial Screening: Submissions are first evaluated by the editorial team to check for relevance, originality, adherence to journal guidelines, and ethical compliance. Manuscripts that do not meet basic standards are desk-rejected.

  2. Reviewer Assignment: Suitable manuscripts are assigned to at least two independent experts in the field of data science, artificial intelligence, or intelligent systems. Reviewers are selected based on their expertise, experience, and academic credentials.

  3. Evaluation Criteria: Reviewers assess manuscripts based on originality, scientific rigor, clarity of presentation, methodological soundness, ethical compliance, and contribution to the field. Constructive feedback is provided to help authors improve their work.

  4. Revision and Resubmission: Authors may be asked to revise and resubmit their manuscripts in response to reviewer comments. The revised manuscript may undergo additional rounds of review until it meets the journal’s standards.

  5. Editorial Decision: The Editor-in-Chief, along with the editorial board, makes the final decision on acceptance, minor/major revisions, or rejection, based on reviewer recommendations and the overall quality of the manuscript.

  6. Ethical Considerations: The journal adheres strictly to COPE (Committee on Publication Ethics) guidelines to handle conflicts of interest, plagiarism, duplicate submissions, and research misconduct.

IJDSS is committed to maintaining integrity, transparency, and fairness throughout the peer review process. By implementing these practices, the journal ensures that every published article contributes significantly to the advancement of knowledge in data science, artificial intelligence, and intelligent systems.