Abstract

Data alteration requires consideration of: what are data, when should they be available and what is their quality. Alteration may be intended or unintended: scientific misconduct, scientific error, use of questionable research practices, or community-based and cultural interpretations of data relevance. Situations in which data alteration are at risk include those in which conflict of interest (and thus potential for bias) is endemic, and those in which powerful incentives that do not support research integrity are present. Consequences of intentional and unintentional data alteration are morally important but are not uniformly addressed. Norm and governance changes from the current system are in initial stages of development and must address issues of the data revolution. Points of decision address ethical concerns and moral quandaries researchers will likely face in a system of research practice that does not comprehensively support research integrity.