Allegations Of Research Misconduct Policy

Mathematical and Data Analytics

Mathematical and Data Analytics is committed to maintaining academic honesty, methodological transparency, data integrity, and ethical standards throughout the publication process.

All allegations of research and publication misconduct will be assessed fairly, objectively, proportionately, and on the basis of available evidence, following the principles of the Committee on Publication Ethics (COPE).

1. Definition and Types of Misconduct

Research and publication misconduct may involve conduct that violates accepted standards of academic honesty, originality, transparency, or scholarly responsibility.

Potential forms of misconduct include:

  1. Plagiarism: Presenting another party’s text, mathematical concepts, theorems, proofs, models, algorithms, source code, figures, or research findings without appropriate acknowledgment.

  2. Data Fabrication: Inventing datasets, observations, simulation outputs, numerical results, statistical estimates, or other research data that were never generated.

  3. Data Falsification: Manipulating, selectively altering, or omitting data, analytical outputs, or research results in a manner that misrepresents the findings.

  4. Misrepresentation of Mathematical Results: Deliberately misrepresenting the validity, originality, assumptions, or scope of mathematical statements, proofs, or derivations, including knowingly concealing substantive limitations or counterexamples.

  5. Manipulation of Statistical Analysis or Model Evaluation: Deliberately misrepresenting sampling methods, statistical tests, validation procedures, dataset partitioning, data leakage, model comparisons, or performance measures. This may include undisclosed selective reporting of analyses intended to create misleading conclusions.

  6. Duplicate or Redundant Publication: Republishing substantially overlapping research without appropriate disclosure, justification, or acknowledgment.

  7. Authorship Misconduct: Misrepresenting author contributions, including inappropriate inclusion or exclusion of contributors.

  8. Peer-Review Manipulation: Fabricating reviewer identities, creating fraudulent reviewer accounts, or improperly influencing editorial evaluation.

  9. Research Ethics and Data Privacy Violations: Using personal, confidential, or restricted data without required authorization, ethical approval, or consent, where applicable.

  10. Copyright and Licensing Violations: Using software, datasets, figures, or other protected materials in violation of applicable permissions or licensing requirements.

Unintentional errors, legitimate mathematical or scientific disagreements, and unsuccessful replication attempts do not automatically constitute research misconduct.

An incorrect proof, a statistical error, or a discrepancy in numerical results may require correction or other editorial action without necessarily indicating misconduct.

Determining whether misconduct has occurred requires appropriate examination of the available evidence and relevant circumstances.

2. Reporting Allegations

Authors, reviewers, editors, readers, researchers, and other stakeholders may report suspected misconduct involving submitted manuscripts or published articles.

Reports should be submitted to:

Editorial Contact: publikasi@itscience.org

Reports should identify the manuscript or article concerned, explain the alleged misconduct, and provide relevant supporting evidence.

Supporting evidence may include substantial textual or mathematical similarities, unattributed proofs or derivations, inconsistent research records, discrepancies in reported datasets, contradictory analytical outputs, reproducible counterexamples, replication results, analysis scripts, or other verifiable documentation.

Mathematical and Data Analytics will consider reports submitted in good faith regardless of the reporter’s academic position or institutional affiliation.

3. Preliminary Assessment

The Editor-in-Chief or a designated editor will conduct a preliminary assessment to determine whether the allegation falls within the journal’s responsibilities and whether sufficient information exists to justify further examination.

This assessment may include similarity screening, examination of mathematical arguments, methodological review, dataset examination, verification of statistical or numerical results, and consultation with relevant subject-matter experts.

For theoretical research, the assessment may consider the assumptions, logical consistency, validity of proofs, attribution of prior results, and scope of the stated conclusions.

For empirical and computational research, the assessment may consider sampling procedures, data preprocessing, model assumptions, statistical methods, validation protocols, software versions, numerical precision, and computational configurations.

A preliminary concern does not constitute a determination of misconduct.

4. Investigation Procedures

When an allegation warrants further examination, Mathematical and Data Analytics will initiate an appropriate editorial investigation.

The process may involve requesting clarification from the authors, reviewing supporting documentation, consulting independent experts, and contacting the authors’ institutions when necessary.

Authors will be given a reasonable opportunity to respond and provide relevant explanations or evidence.

Depending on the nature of the concern, authors may be asked to provide detailed proofs, derivations, original data, data provenance records, analysis scripts, simulation settings, or other materials necessary to assess the reliability and integrity of the research.

Requests for supporting materials will take account of applicable privacy obligations, consent conditions, intellectual property restrictions, and legitimate confidentiality requirements. Where direct disclosure is restricted, the journal may consider appropriate alternatives, such as de-identified materials or verification by an authorized independent party.

Mathematical and Data Analytics will not require the disclosure of passwords, access credentials, or unrelated confidential information.

Where formal investigation exceeds the journal’s authority, the matter may be referred to the relevant institution or competent authority. The journal remains responsible for determining appropriate editorial action concerning submitted manuscripts and published articles.

5. Confidentiality and Protection of Involved Parties

Mathematical and Data Analytics will maintain the confidentiality of allegations, correspondence, and investigative materials to the extent reasonably possible and consistent with applicable obligations.

Access to confidential information will be limited to authorized individuals involved in the assessment.

All parties will be treated fairly, and allegations will not be presented as established misconduct without adequate evidence.

Individuals who report concerns honestly and in good faith should not be subjected to inappropriate retaliation.

6. Editorial Decisions and Corrective Actions

Following the assessment, Mathematical and Data Analytics may take appropriate editorial action depending on the seriousness of the issue and the available evidence.

Possible actions include:

  1. Requesting clarification or manuscript revision.

  2. Rejecting a manuscript before publication.

  3. Publishing a formal correction.

  4. Issuing an Expression of Concern.

  5. Retracting a published article.

  6. Referring the matter to relevant institutions or authorities when appropriate.

  7. Taking other proportionate editorial measures consistent with publication ethics principles.

Editorial decisions will be documented and based on verifiable evidence.

Corrective action may be necessary to address unreliable findings even when deliberate misconduct has not been established. Conversely, an allegation alone will not be treated as sufficient grounds for a finding of misconduct.

When corrective action concerns a published article, an appropriate formal notice will be issued and linked to the relevant publication whenever technically feasible, in accordance with the journal’s Correction and Retraction Policy.

7. Conflicts of Interest and Editorial Independence

Editors, reviewers, and other individuals involved in handling misconduct allegations must disclose relevant conflicts of interest.

Individuals whose impartiality may reasonably be compromised will not participate in the affected assessment or decision.

When an allegation involves the Editor-in-Chief or presents a conflict of interest for that role, responsibility for handling the case will be assigned to an independent editor or another appropriately qualified editorial representative.

Mathematical and Data Analytics will maintain editorial independence and ensure that decisions are not improperly influenced by personal, institutional, or commercial interests.

8. Appeals and Reconsideration

Authors who believe an editorial decision concerning alleged misconduct was based on a material factual or procedural error may submit an appeal to:

Editorial Contact: publikasi@itscience.org

Appeals must include a clear explanation and relevant supporting evidence.

Where feasible, appeals will be assessed by an editor or independent party who was not directly involved in the original decision.

Submitting an appeal does not automatically reverse or suspend the editorial decision.

9. Documentation and Policy Review

Mathematical and Data Analytics will maintain appropriate documentation of allegations, supporting evidence, correspondence, assessments, editorial decisions, and corrective actions.

Records will be stored securely, with access restricted to authorized personnel.

This policy will be reviewed periodically to maintain consistency with developments in publication ethics, mathematical and statistical research practices, responsible data analysis, and COPE guidance.

10. Commitment to Research Integrity

Mathematical and Data Analytics recognizes that research integrity is fundamental to progress in mathematics, statistics, and data-driven research.

The journal is committed to promoting originality, rigorous mathematical reasoning, accurate reporting of analytical and numerical results, methodological transparency, responsible data use, and ethical editorial practices.

All allegations of research misconduct will be handled professionally, fairly, and on the basis of evidence to preserve confidence in the journal’s scholarly publications.