方法对比

	数据共享与开放科学	学术研究中的剽窃
领域	出版伦理	出版伦理
方法族	Process / pipeline	Process / pipeline
起源年份	2010	1989
提出者	Open science movement; Center for Open Science; funding agencies (NIH, EU, NSF)	U.S. Office of Research Integrity (ORI) and institutional policies
类型	Framework	Standard
开创性文献	Open Science Framework (2023). OSF. Center for Open Science.	U.S. Office of Research Integrity (2023). Definition of Research Misconduct. Federal Policy on Research Misconduct (42 CFR Part 93). ORI.
别名	Open Data, Research Data Sharing, Research Reproducibility	Text Plagiarism, Idea Plagiarism, Self-Plagiarism
相关	4	4
摘要	Data sharing and open science are practices that maximize research transparency and reproducibility by making raw data, analysis code, and methods publicly available alongside publications. The replication crisis (widespread failure to reproduce published findings in psychology, medicine, and other fields) revealed that traditional publication—focusing on novel results—incentivizes selective reporting and p-hacking. Open science practices (preregistration, data sharing, code sharing, open materials) aim to reduce bias and enable independent verification. Major funders (NIH, NSF, EU) now mandate open science practices, and many journals require data availability statements or code repositories.	Plagiarism—the use of others' words, ideas, or methods without attribution—is formally classified as research misconduct by the U.S. Office of Research Integrity and most institutions worldwide. It ranges from verbatim copying of text to paraphrasing without citation to presenting others' ideas as one's own. Unlike accidental omission of a citation (which is corrected via erratum), plagiarism implies intent or gross negligence and triggers investigation, potential retraction, and career consequences. Plagiarism detection tools (e.g., Turnitin, iThenticate) and manual checking by journals now routinely screen manuscripts.