Review Policy
Review Policy
Journal of Applied Data Science and Computational Intelligence
The Journal of Applied Data Science and Computational Intelligence is committed to upholding the highest standards of publication ethics, ensuring the scientific rigor, objectivity, and academic integrity of all published research. To maintain these standards, the journal operates a rigorous peer-review system managed by the Editorial Board.
The Journal of Applied Data Science and Computational Intelligence is committed to upholding the highest standards of publication ethics, ensuring the scientific rigor, objectivity, and academic integrity of all published research. To maintain these standards, the journal operates a rigorous peer-review system managed by the Editorial Board.
1. Peer Review Model (Double-Blind)
This journal employs a double-blind peer-review process. To ensure completely unbiased evaluation:
Author Anonymity: The identities of the authors and their affiliations are concealed from the reviewers throughout the review process.
Reviewer Anonymity: The identities of the reviewers are concealed from the authors.
Preparation Requirements: Authors must ensure their manuscripts are fully anonymized prior to submission (e.g., removing author names, institutional affiliations, funding acknowledgments, and explicit self-references from the main text and file metadata).
This journal employs a double-blind peer-review process. To ensure completely unbiased evaluation:
Author Anonymity: The identities of the authors and their affiliations are concealed from the reviewers throughout the review process.
Reviewer Anonymity: The identities of the reviewers are concealed from the authors.
Preparation Requirements: Authors must ensure their manuscripts are fully anonymized prior to submission (e.g., removing author names, institutional affiliations, funding acknowledgments, and explicit self-references from the main text and file metadata).
2. Reviewer Allocation and Requirements
Expert Evaluation: Every manuscript passing initial editorial screening is assigned to a minimum of three (3) independent reviewers who possess specialized domain knowledge in the relevant subfield.
Selection Criteria: Reviewers are selected based on their technical expertise, active publication record in relevant disciplines (such as machine learning, deep learning, data engineering, soft computing, and computational optimization), and absolute absence of conflicts of interest.
Expert Evaluation: Every manuscript passing initial editorial screening is assigned to a minimum of three (3) independent reviewers who possess specialized domain knowledge in the relevant subfield.
Selection Criteria: Reviewers are selected based on their technical expertise, active publication record in relevant disciplines (such as machine learning, deep learning, data engineering, soft computing, and computational optimization), and absolute absence of conflicts of interest.
3. The Peer Review Process
The journal follows a structured workflow to guarantee a thorough, transparent, and fair evaluation:
Initial Editorial Desk Review: Upon submission, the Editor-in-Chief or a designated Managing Editor assesses the paper for alignment with the journal’s scope, adherence to formatting guidelines, and baseline technical merit. Manuscripts are also automatically screened for plagiarism and duplicate submission at this stage.
Anonymized Reviewer Assignment: Manuscripts meeting initial quality standards are anonymized and distributed to at least three external subject-matter experts.
Evaluation Framework: Reviewers evaluate submissions using the following criteria:
Novelty & Significance: Originality of the computational techniques, algorithms, or data science applications.
Technical & Algorithmic Rigor: Validity of datasets, experimental design, baseline comparisons, mathematical formulation, and reproducibility.
Clarity & Structure: Logical organization, precise technical communication, clear visualization of results, and English language proficiency.
Ethical Compliance: Proper citation of prior work, appropriate data governance, and ethical AI practices.
Editorial Decision: Upon receiving at least three detailed review reports, the Handling Editor synthesizes the feedback and recommends an editorial decision. Final approval rests with the Editor-in-Chief.
The journal follows a structured workflow to guarantee a thorough, transparent, and fair evaluation:
Initial Editorial Desk Review: Upon submission, the Editor-in-Chief or a designated Managing Editor assesses the paper for alignment with the journal’s scope, adherence to formatting guidelines, and baseline technical merit. Manuscripts are also automatically screened for plagiarism and duplicate submission at this stage.
Anonymized Reviewer Assignment: Manuscripts meeting initial quality standards are anonymized and distributed to at least three external subject-matter experts.
Evaluation Framework: Reviewers evaluate submissions using the following criteria:
Novelty & Significance: Originality of the computational techniques, algorithms, or data science applications.
Technical & Algorithmic Rigor: Validity of datasets, experimental design, baseline comparisons, mathematical formulation, and reproducibility.
Clarity & Structure: Logical organization, precise technical communication, clear visualization of results, and English language proficiency.
Ethical Compliance: Proper citation of prior work, appropriate data governance, and ethical AI practices.
Editorial Decision: Upon receiving at least three detailed review reports, the Handling Editor synthesizes the feedback and recommends an editorial decision. Final approval rests with the Editor-in-Chief.
4. Possible Outcomes
Authors will receive an official decision letter accompanied by anonymized feedback from all assigned reviewers:
Accept As Is: The manuscript is accepted for publication without additional changes.
Minor Revisions: The authors must address minor technical clarifications, formatting updates, or minor algorithm adjustments within a specified timeframe.
Major Revisions: The paper requires substantial reworking—such as additional experimental validation, algorithmic refinement, or expanded baseline comparisons. Revised submissions are typically re-evaluated by the original reviewers.
Reject: The manuscript is declined due to major technical flaws, insufficient novelty, lack of empirical validation, or irrelevance to the journal's focus areas.
Authors will receive an official decision letter accompanied by anonymized feedback from all assigned reviewers:
Accept As Is: The manuscript is accepted for publication without additional changes.
Minor Revisions: The authors must address minor technical clarifications, formatting updates, or minor algorithm adjustments within a specified timeframe.
Major Revisions: The paper requires substantial reworking—such as additional experimental validation, algorithmic refinement, or expanded baseline comparisons. Revised submissions are typically re-evaluated by the original reviewers.
Reject: The manuscript is declined due to major technical flaws, insufficient novelty, lack of empirical validation, or irrelevance to the journal's focus areas.
5. Confidentiality and Ethics
Confidentiality: Manuscripts, reviewer reports, and editorial correspondence are strictly confidential. Reviewers are forbidden from retaining, copying, sharing, or utilizing any unpublished ideas, code, or datasets presented in the paper.
Conflict of Interest: Reviewers must immediately declare any financial, institutional, personal, or collaborative conflicts of interest to the editorial team and recuse themselves if objectivity cannot be guaranteed.
Ethical Standards: The journal adheres strictly to the principles set by the Committee on Publication Ethics (COPE). Allegations of plagiarism, data fabrication, improper code manipulation, or unauthorized use of generative models will be investigated immediately.
Confidentiality: Manuscripts, reviewer reports, and editorial correspondence are strictly confidential. Reviewers are forbidden from retaining, copying, sharing, or utilizing any unpublished ideas, code, or datasets presented in the paper.
Conflict of Interest: Reviewers must immediately declare any financial, institutional, personal, or collaborative conflicts of interest to the editorial team and recuse themselves if objectivity cannot be guaranteed.
Ethical Standards: The journal adheres strictly to the principles set by the Committee on Publication Ethics (COPE). Allegations of plagiarism, data fabrication, improper code manipulation, or unauthorized use of generative models will be investigated immediately.
"Journal of Applied Data Science and Computational Intelligence."
Editor in Chief- Dr. Muhammad Aminul Haque Akhand
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