GENERAL PRINCIPLE FOR ENSURING THE INTEGRITY OF RESEARCH DATA

The new capabilities and challenges posed by digital technologies point to the need for a renewed emphasis on data integrity. The assumption that traditional practices will suffice is no longer tenable as digital technologies continue to transform the nature of research. Researchers must be aware of how the integration of digital technologies into research affects the quality of data. As the generation and dissemination of data become the primary objectives of some research projects, researchers need to find ways to validate the quality of those data. They need to take steps to ensure that digital technologies enhance rather than detract from data integrity.

These observations lead to the following general principle:


Data Integrity Principle: Ensuring the integrity of research data is essential for advancing scientific, engineering, and medical knowledge and for maintaining public trust in the research enterprise. Although other stakeholders in the research enterprise have important roles to play, researchers themselves are ultimately responsible for ensuring the integrity of research data.


In emphasizing the importance of this principle, the committee is not calling for formal assurances of data integrity. Maintaining the quality of research is an essential part of being a responsible and competent researcher. In assigning researchers the ultimate responsibility for data integrity, the committee is asking no more than that researchers adhere to the standards established and held in common by all researchers.

This principle may seem apparent, but its application in the digital age leads to several important recommendations.

THE OBLIGATIONS OF RESEARCHERS TO ENSURE THE INTEGRITY OF RESEARCH DATA

Researchers have a fundamental obligation to their colleagues, to the public, and to themselves to ensure the integrity of research data. Members of the research community trust that their colleagues will adhere to the standards of their field and will be transparent in describing the methods used to generate data. They also assume that colleagues will make available the data on which publicly disseminated research results are based. (Chapter 3 discusses issues of data access in detail.) Members of the general public may be unfamiliar with the standards of a research field, but they, too, trust that researchers will gather, analyze, and review data accurately, honestly, and without unstated bias. If trust among colleagues or the public is misplaced and research data are shown to be inaccurate (or, even worse, fabricated), the consequences can be severe both within science and in the broader society.



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