Plagiarism

Plagiarism Checking Policy

The Journal of Data Science and Education (JDSEDU) is committed to maintaining the highest standards of academic integrity and ethical publishing. All submitted manuscripts are subject to plagiarism screening to ensure the originality of the work.

JDSEDU utilizes reliable plagiarism detection tools such as Turnitin and/or iThenticate to evaluate the similarity index of each submission.

 

1. Similarity Threshold

  • Manuscripts must have a similarity index below 20% (excluding references, quotations, and methodological phrases).
  • A similarity index above the threshold will be evaluated carefully to determine the nature of the overlap.
  • High similarity due to self-plagiarism, redundant publication, or improper citation may lead to rejection.

2. Types of Plagiarism Considered

The journal identifies and does not tolerate the following forms of plagiarism:

  • Direct Plagiarism: Copying text without proper citation
  • Self-Plagiarism: Reusing one's previously published work without acknowledgment
  • Mosaic Plagiarism: Paraphrasing content without proper attribution
  • Data Plagiarism: Using data or results without permission or citation

3. Screening Process

  • All manuscripts are screened before peer review.
  • Editors may re-check manuscripts after revision.
  • If plagiarism is detected at any stage, appropriate actions will be taken.