Research fraud prevention and data integrity

Maintain research integrity and prevent scientific misconduct. Types of misconduct: 1. Fabrication: making up data or results. 2. Falsification: manipulating research processes or changing results. 3. Plagiarism: using others' ideas without proper attribution. 4. Questionable research practices: p-hacking, selective reporting, inappropriate authorship. Prevention strategies: 1. Research integrity training: responsible conduct of research courses. 2. Data management: audit trails, version control, shared databases. 3. Supervision: regular meetings, progress reviews, co-analysis of data. 4. Institutional culture: open discussion of ethical dilemmas, reporting mechanisms. Detection methods: 1. Statistical screening: digit analysis, impossible values, too-perfect distributions. 2. Image analysis: duplicated images, inappropriate manipulation. 3. Text analysis: plagiarism detection software. 4. Peer review: careful examination of methods and results. Response protocols: 1. Investigate allegations promptly and fairly. 2. Protect whistleblowers from retaliation. 3. Collaborate with journals for corrections or retractions. Restoration: focus on education and prevention rather than punishment alone.