Data-Intensive Science and Research Integrity

David B. Resnik, Kevin C. Elliott, Patricia A. Soranno, Elise M. Smith

Research output: Contribution to journalComment/debate

Abstract

In this commentary, we consider questions related to research integrity in data-intensive science and argue that there is no need to create a distinct category of misconduct that applies to deception related to processing, analyzing, or interpreting data. The best way to promote integrity in data-intensive science is to maintain a firm commitment to epistemological and ethical values, such as honesty, openness, transparency, and objectivity, which apply to all types of research, and to promote education, policy development, and scholarly debate concerning appropriate uses of statistics.

Original languageEnglish (US)
Pages (from-to)344-358
Number of pages15
JournalAccountability in Research
Volume24
Issue number6
DOIs
StatePublished - Aug 18 2017
Externally publishedYes

Keywords

  • Data-intensive science
  • deception
  • education
  • ethics
  • misconduct
  • research integrity
  • transparency

ASJC Scopus subject areas

  • Education
  • Library and Information Sciences

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