“Only the Initiates Will Have the Secrets Revealed”: Computational Chemists and the Openness of Scientific Software

Abstract

Computational chemistry is a scientific field within which the computer is a pivotal element. This scientific community emerged in the eighties and was involved with two major industries: the computer manufacturers and the pharmaceutical industry, the latter becoming a potential market for the former through molecular modeling software packages. We aim to address the difficult relationships between scientific modeling methods and the software implementing these methods throughout the nineties. Developing, using, licensing and distributing software leads to multiple tensions among the actors in intertwined academic and industrial contexts. The Computational Chemistry mailing List (CCL), created in 1991, constitutes a valuable corpus for revealing the tensions associated with software within the community. We analyze in detail two flame wars which exemplify these tensions. We conclude that models and software must be addressed together. Interrelations between both imply that openness in computational science is complex.1 Keywords scientific software, computational chemistry, software users, openness, history of chemistry, mailing list, flame warsThe quotation in the title, taken from a scientific mailing list, the "Computational Chemistry List", is intended to illustrate the tensions around the use of software in a scientific community. "Computational chemists", gathered around the uses of computers in chemistry [1], belong to a scientific field which started to grow in the eighties, whose aim was to develop "computational tools and techniques [which] offer a new method of attack in the continuing effort [in the chemical community] to obtain chemical information" [2]. Thus, the computer is a pivotal element of this scientific community, even though it is considered here as a tool, not as the object of the science in question. The adjective "computational", a typical word from the eighties and nineties, is essential: it is a scientific world of "computational science", not "computer science".Numerous studies deal with the relations between computing and scientific activity, some of which are even considered as classics. Themes such as the "computerization of science" [3] or, for example, the mutual shaping of computing and biology [4] or the emergence of computerized evidence-based medicine [5] explore their interplay. Computational science has been addressed by scholars, for example the philosophical significance of its rise for scientific method [6], or the emergence of Monte Carlo simulations [7]. Many works also exist in the history of software [8], either on the software viewed as an industrial [9] or professional [10] activity, or on the difficulty and complexity of writing such a history [11]. Yet, software per se in computational science has attracted less attention, even if Spencer has conducted an ethnographic research within a computational fluid dynamics laboratory on a piece of software [12].Our way to address the issue of software in computational science is to focus on application software in computat...

A tale of two 'opens': intersections between Free and Open Source Software and Open Scholarship

“…We recognise movements of convergence as well as divergence in their shared history. For example, software and data accessibility (e.g., availability, inspection, and re-use) are now considered prerequisite for making full research environments transparent and rigorous enough to reproduce results (Ghosh et al 2012;Sandve et al 2013;Millman and Perez 2014;Hocquet and Wieber 2018). Many modern data collection and analysis workflows, including preparation and dissemination of publications, rely on a range of essential software or Web-based tools for which powerful FOSS solutions already exist (e.g., R , Python , Julia , GNU PSPP ).…”

Models, Parameterization, and Software: Epistemic Opacity in Computational Chemistry

“…These tasks, bundled into the wording "parameterization," are, in computational chemistry, an arduous enterprise as we will show in a historical account further into this text, and we argue that this activity leads to tensions among scientists regarding the lack of epistemic transparency of parameterized methods and the software implementing them. We have analyzed previously the multiple tensions among the scientists in this community who develop, license, distribute, and use software in intertwined academic and industrial contexts (Hocquet and Wieber 2017). In the present paper, we emphasize the epistemological issues at stake, specifically regarding epistemic opacity within the pivotal issue of parameterization.…”

“…In the 1980s and 90s, when the Personal Computer and the workstation made computation more widely available in the laboratory, a new era of "desktop modeling" (Johnson and Lenhard 2011) coincided with a growing demand for modeling software, especially from the pharmaceutical industry (Richon 2008). The molecular modeling software became a huge potential market for hardware manufacturers to sell graphics terminals and computing power to Big Pharma, that was eager to dive into the techno-scientific promise of "rational drug design" (Hocquet and Wieber 2017). Moreover, in the 1980s, during the Reagan years, the universities (in the US at least) launched "technology transfer" programs.…”

“We were here before the Web and hype…”: a brief history of and tribute to the Computational Chemistry List

“…Pisanty and Labanowski had led a survey of membership from which some of the above conclusions were extracted [4], and Labanowski published about the difficult role of moderator on the CCL [5]. Hocquet and Wieber have more recently discussed the history and activity of the CCL [6]. They have for example explored aspects such as the performative functions of language in the list on the one hand and discourse structure on the other [7].…”

“…In the CCL, this pidgin is perfectly suited to the diversity of topics of concerns to a professionally diverse community. It is notable that most conversations revolve around software as a topic, at the intersection of theories/modelling methods/publications/coding/software support and maintenance/licensing/hardware benchmarking/sales [6].…”