Lies, Damned Lies and Research Data: Can Data Sharing Prevent Data Fraud?

Abstract

After a spectacular case of data fraud in the field of social psychology surfaced in The Netherlands in September 2011, the Dutch research community was confronted with a number of questions. Is this an isolated case or is scientific fraud with data more common? Is the scientific method robust enough to uncover the results of misconduct and to withstand the breach of trust that fraud causes? How responsible and reliable are researchers when they collect, process, analyse and report on data? How can we prevent data fraud? Do we need to adapt the codes of conduct for researchers or do we need stricter rules for data management and data sharing?This paper discusses the conclusions and recommendations of two reports that were published recently in consequence of this data fraud. The reports are relevant for scientific integrity and trustworthy treatment of research data. Next, this paper reports on the outcomes of enquiries in data cultures in a number of scientific disciplines. The concluding section of this paper contains a number of examples that show that the approach towards data sharing is improving gradually. The data fraud case can be regarded as a wake-up call.

Business models for sustainable research data repositories

“…A fundamental principle for research quality and integrity is the ability of others to verify the results by checking the data used to derive the research findings and to avoid fraud. The underlying data need to be broadly available for verification and reproducibility of results, sometimes even many years after their publication (Doorn, 2013;NRC, 2009bNRC, , 2004NRC, , 2003NRC, , 1999NRC, , 1997.…”

Analyzing data citation practices using the data citation index

“…If data sharing is to become a common practice, a change in the culture and research process will have to take place. It may protect against scientific fraud and improve the scientific method, but only if such data are managed and shared correctly (Doorn, Dillo, & van Horik, ). One way of encouraging data sharing is by establishing a reward system by which researchers see a benefit to their efforts and the time invested.…”

DataCite as a novel bibliometric source: Coverage, strengths and limitations

“…A similar expansion can be observed in Genomics or Astronomy (Borgman, 2012). On the other hand, social sciences and the humanities have thus adopted these new practices at a slower pace than STEM fields (Doorn, Dillo, & van Horik, 2013;Kim & Adler, 2015).…”