Anti-Plagiarism Policy of JZUS-A/B&FITEE

© Journals of Zhejiang University-SCIENCE 2015    Version dated 11 May 2015

Nine basic forms of plagiarism

•  Self- (or team) plagiarism without identification and acknowledgement

•  Cutting and pasting of others' work without identification and acknowledgement

•  Replication of methods sections (in Biomedical journals) without clear statement of the source

•  Republication of conference papers with little added value

•  Review papers which largely replicate previously published content

•  Plagiarism of images/tables/formulae/data without both acknowledgement and copyright permission

•  Plagiarism of ideas

•  Wholesale plagiarism of previously published text

•  Republication in translation without acknowledgment, permission and full citation

Anti-Plagiarism Policy

The general rules that we have come up with are as follows:

The following are acceptable, provided always that (a) the quotation (if any) is typographically identified (by quotation marks or, for longer extracts, indentation), (b) the source is acknowledged in the text, and (c) a full citation to the original is given:

(1)  Quotation of a modest amount (under 100 words) of the author’s own or others’ text;

(2)  Paraphrase of previously published text in the author’s own words;

(3)  Repetition of someone else’s ideas;

(4)  Reproduction of a chart, image, table or key equation from your own or someone else’s work (provided copyright permission has been obtained from the original copyright owner, and acknowledgement is included in whatever form they request);

(5)  In Biosciences papers it is acceptable to reproduce the description of a standard/homemade method from a previously published source, provided the source is properly acknowledged;

(6)  Republication of a previously published conference paper is acceptable, if 60% or more of the content is new and substantive (provided copyright permission has been obtained from the original copyright owner, and acknowledgement is included in whatever form they request).

The following are unacceptable in any circumstances:

(7)  Duplicate publication of an entire article;

(8)  Major plagiarism of the work of others (SMSI>10 % or OSI>35%);

(9)  Serious self (or team)-plagiarism (SMSI>10% or OSI>35%);

(10)  Review papers which reproduce substantial amounts of the texts discussed (OSI>35%).

Anti-Plagiarism Policy of Journals of Zhejiang University-SCIENCE (JZUS-A/B&FITEE)


Ethical requirement available here :

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Text and Data Mining (TDM) Policy

Version dated 15 Apr. 2015

Journal of Zhejiang University-SCIENCE (JZUS) recognizes that text and data mining (TDM) is increasingly seen as a useful method for analyzing large volumes of unstructured documents, which can meet the needs of researchers and support the innovation and development of new knowledge. JZUS participates in CrossRef Text and Data Mining Services. Researchers are able to text mine content accessed via CrossRef and Springer’s Metadata API. Our current policy will be updated from time to time.

Terms and conditions for TDM

JZUS grants TDM rights to subscribed contents since 2015. These terms and conditions shall be accepted by anyone granted access to JZUS’s website ( for TDM purposes.

1. TDM access is provided to subscribers only for noncommercial research purposes.

2. Outputs of anything generated directly by TDM must be licensed by the user under a Creative Commons CC-BY license, Version 3.0 (

3. Output can include snippets of up to a maximum of 200 characters from the original text, excluding text entity matching or bibliographic metadata.

4. The selection and refinement of desired articles can be conducted by using existing search methods and tools, such as CrossRef and Springer’s Metadata API. Full-text contents can be accessed easily and programmatically at URLs based on the articles’ DOIs.

TDM agreement

Text mining access for subscription content is provided to subscribers for noncommercial research purposes. Once a click through agreement is accepted, JZUS grants the researchers to access data obtained available by the API and will deliver the API documentation using query algorithms (e.g., curl, Python) and cryptographic API keys through CrossRef Text and Data Mining Services.

We are glad to accommodate if any researchers who have specific text mining needs. Please email to,

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