Review Model

 

Journal of Computer and Data Science (JCODA) adopts a double-anonymous peer-review model in which, where practicable, the identities of authors and reviewers are concealed from each other throughout the review process. This approach promotes impartial assessment and helps minimize potential bias in scholarly evaluation.

Double-Anonymous Review

  • Authors are not informed of the identities of the reviewers.
  • Reviewers are not provided with the authors' identities through the journal's review process.
  • Review reports and editorial communications are treated as confidential documents.
  • Reviewer identities are not disclosed to authors unless the journal explicitly establishes a different procedure.

Reviewer Selection

Reviewers are selected based on their subject expertise, research experience, relevant publication record, methodological competence, and ability to provide an independent assessment. Potential conflicts of interest are considered when identifying suitable reviewers.

Reviewer Independence

Reviewers must provide objective, evidence-based, and constructive evaluations. Personal, institutional, financial, ideological, or professional relationships must not compromise their judgment. Reviewers should disclose any circumstances that could affect the impartiality of their assessment.

Conflict of Interest

Reviewers must decline an invitation if an actual, potential, or perceived conflict of interest could compromise the impartiality of their review. If a relevant conflict becomes apparent after accepting the assignment, reviewers must promptly inform the editor so that appropriate action can be taken.

Confidentiality

Reviewers must not disclose, distribute, reproduce, or use unpublished information contained in a manuscript for personal, research, financial, or professional advantage. Manuscripts and review materials must remain confidential and must not be shared with unauthorized individuals. These obligations continue after the review assignment has ended.