Data Integrity and Plagiarism Services

Scientific documents sometimes contain serious errors in data, analysis or text, either because of honest mistakes or because of deliberate fraud. Combining informatics tools with the insight of our experts, we uncover potential problems for scientific publishers and journals, academic institutions, public bodies, industry. We check for:

  • Improper image manipulations
  • Number fabrication and manipulated statistics
  • Text plagiarism

Consulting in Potential Misconduct Cases

Universities, scientific institutions and government offices often lack the necessary definitions, regulations, legal frames and technologies to deal with academic misconduct. Building on our extensive knowledge, we help to solve cases and put in place the right procedures and guidelines to mitigate the risk of future misconduct. We have experience in cases involving:

  • Academic and scientific bodies
  • Scientific agencies
  • Government bodies

Education and Advocacy

Educating the next generation of researchers, helping senior investigators to put in place a proper data integrity pipeline and deploying the appropriate technologies - these are all crucial steps in improving the reproducibility and reliability of science. Moreover, we engage with the general public about scientific integrity, as part of a broad effort to restore trust in the scientific community. We are routinely active in:

  • Delivering university courses on research integrity
  • Communicating at meeting and forums
  • Communicating on mass media

Research into Scientific Misconduct

How much of published data is unreliable? How many scientists cheat? Which technologies could be developed to detect and prevent fraudulent manipulations? We believe that only science can provide the correct answers. That is why we are engaged in projects aimed to build better tools and to study fraud in science. Main fields of active interest for Resis srl are the following:

  • Large scale analysis of scientific documents
  • Image analytics for fraud detection
  • Ethics of scientific research