This paper reflects on the relation between international debates around data quality assessment and the diversity characterising research practices, goals and environments within the life sciences.
Since the emergence of molecular approaches, many biologists have focused their research, and related methods and instruments for data production, on the study of genes and genomes.
While this trend is now shifting, prominent institutions and companies with stakes in molecular biology continue to set standards for what counts as ‘good science’ worldwide, resulting in the use of specific data production technologies as proxy for assessing data quality.
This is problematic considering (1) the variability in research cultures, goals and the very characteristics of biological systems, which can give rise to countless different approaches to knowledge production; and (2) the existence of research environments that produce high-quality, significant datasets despite not availing themselves of the latest technologies.
Ethnographic research carried out in such environments evidences a widespread fear among researchers that providing extensive information about their experimental set-up will affect the perceived quality of their data, making their findings vulnerable to criticisms by better-resourced peers. T
hese fears can make scientists resistant to sharing data or describing their provenance. To counter this, debates around Open Data need to include critical reflection on how data quality is evaluated, and the extent to which that evaluation requires a localised assessment of the needs, means and goals of each research environment.
Authors : Nadine Levin, Sabina Leonelli, Dagmara Weckowska, David Castle, John Dupré
This article documents how biomedical researchers in the United Kingdom understand and enact the idea of “openness.”
This is of particular interest to researchers and science policy worldwide in view of the recent adoption of pioneering policies on Open Science and Open Access by the U.K. government—policies whose impact on and implications for research practice are in need of urgent evaluation, so as to decide on their eventual implementation elsewhere.
This study is based on 22 in-depth interviews with U.K. researchers in systems biology, synthetic biology, and bioinformatics, which were conducted between September 2013 and February 2014.
Through an analysis of the interview transcripts, we identify seven core themes that characterize researchers’ understanding of openness in science and nine factors that shape the practice of openness in research.
Our findings highlight the implications that Open Science policies can have for research processes and outcomes and provide recommendations for enhancing their content, effectiveness, and implementation.