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US President Donald Trump has quickly become a major source of concerns and annoyance among scientists since he took office last year. His various actions and announcements—from barring scientists from various Muslim countries from entering the USA to his proposed budget cuts for research to his personnel decisions for federal agencies—have prompted scientists to take it to the streets in unprecedented numbers. From Washington DC to Busan, South Korea and from Sydney, Australia to Berlin, Germany, between 300,000 and 500,000 participants at the March of Science shouted slogans and placated posters on Earth Day, April 22 (Fig 1). While President Trump's rhetoric and policies provided the stimulus, a general feeling that science has become irrelevant in politics, whether in the heat of political campaigns, or in the day‐to‐day governing of a country, further fuelled and supported scientists’ engagement. Figure 1. March for Science in Washington, DC, USA, 22 April 2017 Image by Paul Becker, Grove City, OH, USA, under the terms of a CC‐BY license. The content of the article does not necessarily represent the photographer's opinion. > The Trump administration has not just regarded science as merely inconvenient but taken an openly hostile attitude to research that does not fit into its political agenda. Yet, Trump is not the first US president to draw the ire of scientists. US President George W. Bush was perceived as the anti‐science president given his scepticism of climate change, his tolerance for teaching intelligent design in school and his general disdain for scientific advice: science was “an annoying inconvenience to its political agenda; an inconvenience that needed to be ignored, suppressed or even manipulated for political purposes” [1]. Throughout both of President Bush's terms, scientists argued and voiced their concerns. However, none of those protests and arguments ever rose to the scale of the March for Science on April 22. The Trump administration has …

The new field of research into the ethical, legal and social aspects of scientific and technological developments (ELSA) is rapidly becoming a professional field with grants, research programmes and university departments devoted to it. At first glance, ELSA seems to be a new development intended to address questions and challenges that arise from advances in the natural sciences. The professionalization of ELSA resembles that of ‘the history of science’, a research field that emerged at the end of the Second World War. The promise that ELSA makes—that it can reacquaint science with society, and the natural sciences with the humanities and the social sciences—was actually first made by science historians in the first half of the twentieth century (van Berkel, 1988). However, although science historians are thought to have failed in respect to this promise, they did manage to craft a new profession at the intersection of science and society (van Berkel, 1988). The question is whether ELSA will be able to succeed where the history of science failed, or whether history will repeat itself. Reflections on the relationship between science and society are not new, but it is only recently that these have received systematic attention from both scientists and non‐scientists. In addition, the public and policy‐makers increasingly demand that large‐scale research programmes or technological advances should be accompanied by studies of their potential social, political and legal impact. This trend probably began when Nobel laureate James Watson announced that the Human Genome Project would devote a significant amount of its funding to study the so‐called ethical, legal and social issues (ELSI) of the full human genome sequence (Kitcher, 2001). Inspired by ELSI and further motivated by a desire not to inflame the public—as happened with GM crops or stem‐cell research, for example—many contemporary international large‐scale research initiatives have …

Last year, Geoffrey Chang and co-workers retracted five papers that contained a faulty protein structure prediction—the result of an error in their software (Chang et al, 2006). Although the ensuing debates and arguments about this ‘great pentaretraction' have slowly dissipated, it is useful to shed some light on the context in which such mistakes occur. We believe that there are fundamental differences in the scientific philosophy and methodology underlying the discussion that cannot and should not be explained by current definitions of good or bad science. This is not exclusive to protein crystallography; it is also typical of other large-scale, high-tech research fields including nanotechnology, systems biology and imaging technologies. In general, structural biology is a ‘hot' research field, involving the constant development of analytical approaches and technologies—combinations of two specific styles of science (Hacking, 1992): classical ‘wet' bench work, and ‘dry' computational and mathematical work. Each style of science—wet and dry—represents a framework for getting at the truth, and comes with its own scientific method, distinct protocols, technologies, theories, language and more general ‘ways of doing'. Consequently, it is possible to make claims within one style that make no sense from the viewpoint of the other. For example, the claim that “MsbA is a member of the MDR–ABC transporter group by sequence homology” (Chang & Roth, 2001) is the result of an in silico comparison of sequences that can neither be performed at the bench, nor understood or proven by wet work alone. This implies that wet and dry science differ in terms of what their proponents regard as ‘proper science'. In an article in Science, Chris Miller, from the Howard Hughes Medical Institute (Waltham, MA, USA), wrote that structures are “just models, not data” and argued that the danger lies in “ignoring biochemical results, conventional but logically solid” (Miller, 2007). He was clearly commenting on the pentaretraction from a wet point of view. From a dry perspective, comments about the error were generally less harsh. It is a widely accepted practice—necessary for doing dry science—to trust a model or an algorithm and believe the outcome. Consequently, dry scientists have generally attributed the error resulting in the Chang retractions to bad luck, an honest mistake, or ‘much ado about nothing'. Conversely, the wet community has tended to use more harsh terms including: debacle, fiasco, monumental blunder, sloppy science and inexcusable. In scientific fields such as structural biology, wet and dry styles are becoming increasingly interdependent. As the complexity of their data far exceeds the computing ability of the human mind, scientists have no choice but to trust computer models. This interaction has become commonplace to a level at which claims, technologies and tools are no longer either wet or dry. They can only be understood and used within a new framework or style that we call ‘moist' science—an integration of dry and wet styles. Accordingly, moist science creates a new way of doing ‘proper science'. Critiques directed at Chang and co-workers exclusively from a dry or a wet point of view therefore cannot fully evaluate the ‘properness' of their research, or fully assess the magnitude of any mistakes. As moist science is a science in the making, some of its technologies are still experimental and protocols have not yet been unanimously accepted. The specific criteria for what it deems to be ‘proper science', or what exactly counts as a mistake, have not yet been set. For example, should the code of an algorithm—which in this case created the error—be included in the methods section of a publication, or made available as supplementary material online? This and other questions must be settled in order to reach a new consensus on what constitutes ‘proper science'. Therefore, the lesson is not whether to blame, but how to learn from and improve on this new moist scientific style.