The Journal of Data Science and Artificial Intelligence is the first journal of the International Society of Data Scientists, with ISSN 2831-4794, to meet the needs for publications by Data Science and AI professionals. We publish peer-reviewed articles reporting on research, development, and applications of Deep Learning and Machine Learning in various areas.

Review Policy

Peer review is an essential aspect of ensuring the quality of scientific publications. To maintain the high standards of the Journal of Pragmatics, all incoming manuscripts undergo a peer review process following the outlined procedure. This objective method of evaluating scholarly work is adopted by all reputable scientific journals.

Initially, one of the Chief Editors evaluates all submitted manuscripts, and in exceptional cases, an outstanding manuscript may be accepted at this stage. Manuscripts that fail to meet the minimum criteria, such as insufficient originality, serious scientific flaws, poor grammar or language, or falling outside the journal's scope, are rejected. Manuscripts that meet the minimum criteria are typically sent to reviewers for reviewing.

1. Selection of reviewers

The selection of reviewers is based on their expertise, and we strive to match them to papers whenever possible. While we continuously update our reviewer database, we welcome recommendations from the author(s) regarding potential reviewers. However, these suggestions are not necessarily used and are considered non-binding.

2. Confidentiality

The utmost confidentiality must be maintained for all manuscripts received for review, and they should be treated as confidential documents. Participants in the review process must be protected and their confidentiality should be ensured.

3. Final decision

The author will receive a final decision on whether the manuscript has been accepted or rejected, along with the recommendations provided by the reviewers, which may include their exact comments if relevant. The Chief Editor's decision is final.