For Reviewers

In order to ensure a high standard of publication, all papers submitted to the Journal of Data Science and Intelligent Systems will undergo peer review before acceptance for publication. The review process ensures that papers are original, substantial, new, and presented effectively.

All submissions should be evaluated objectively, regardless of the writers' affiliation, color, gender, ethnicity, or religion. Your review should be neutral, please avoid making offensive comments about the work or its authors.

Confidentiality

Please do not disclose any information obtained during the peer-review process, or use the unpublished materials in your research without the written consent of the Author as the paper should be treated as confidential.

Conflicts of Interest

You should disclose any potential conflicts of interest and consult with the journal if you are unsure whether or not something constitutes a relevant interest.

Review Criteria

The following criteria must be evaluated by reviewers when evaluating submitted articles. The criteria include questions on research significance, methods, the availability of the data, proper reference, presentation, and key points.

  1. Originality: Does the paper contain new and significant information adequate to justify publication?
  2. Relationship to Literature: Does the paper demonstrate an adequate understanding of the relevant literature in the field and cite an appropriate range of literature sources? Is any significant work ignored?
  3. Methodology: Is the paper's argument built on an appropriate base of theory, concepts, or other ideas? Has the research or equivalent intellectual work on which the paper is based been well designed? Are the methods employed appropriate?
  4. Results: Are results presented clearly and analysed appropriately? Do the conclusions adequately tie together the other elements of the paper？
  5. Implications for research, practice and/or society: Does the paper identify clearly any implications for research, practice and/or society? Does the paper bridge the gap between theory and practice? 
  6. Quality of Communication: Does the paper clearly express its case, measured against the technical language of the field and the expected knowledge of the journal's readership? Has attention been paid to the clarity of expression and readability, such as sentence structure, acronyms, etc.