This article provides an ethnographic account of how Big Data biology is produced, interpreted, debated, and translated in a Big Data-driven cancer clinical trial, entitled “Personalized OncoGenomics,” in Vancouver, Canada. We delve into epistemological differences between clinical judgment, pathological assessment, and bioinformatic analysis of cancer. To unpack these epistemological differences, we analyze a set of gazes required to produce Big Data biology in cancer care: clinical gaze, molecular gaze, and informational gaze. We are concerned with the interactions of these bodily (...) gazes and their interdependence on each other to produce Big Data biology and translate it into clinical knowledge. To that end, our central research questions ask: How do medical practitioners and data scientists interact, contest, and collaborate to produce and translate Big Data into clinical knowledge? What counts as actionable and reliable data in cancer decision-making? How does the explicability or translatability of genomic Big Data come to redefine or contradict medical practice? The article contributes to current debates on whether Big Data engenders new questions and approaches to biology, or Big Data biology is merely an extension of early modern natural history and biology. This ethnographic account will highlight how genomic Big Data, which underpins the mechanism of personalized medicine, allows oncologists to understand and diagnose cancer in a different light, but it does not revolutionize or disrupt medical oncology on an institutional level. Rather, personalized medicine is interdependent on different styles of thought, gaze, and practice to be produced and made intelligible. (shrink)

ArgumentTemporal issues appear to be crucial to the relationship between life scientists and their field sites and to the making of science in the field. We elaborate on the notion of practices of time to describe the ways life scientists cope with multiple and potentially conflicting temporal aspects that influence how they become engaged and remain engaged in a field-site, such as pleasure, long-term security, scientific productivity, and timeliness. With this notion, we seek to bring enhanced visibility and coherence to (...) the extensive but rather scattered and limited treatments of temporal practices in field sciences that already exist. (shrink)

This paper describes the scientific practices of the anatomists from the Société Anatomique de Paris (1803–1873) who were collecting anatomical and pathological specimens in Nineteenth-Century Paris and which led to the building of the anatomy and pathology Musée Dupuytren (1835–2016). The framework introduced by Robert Kohler to describe collecting sciences (2007) is useful as a tool to identify the set of diverse practices within pathological anatomy in nineteenth-century Paris. However, I will argue that anatomy and pathology collecting had specific features (...) compared to most collecting sciences. Two main collecting practices could be distinguished: first, “finding” anatomical specimens and second, keeping these specimens. The first kind of practices were at least rhetorically and explicitly motivated by Auguste Comte’s positive philosophy. But “finding” an anatomy or pathology specimen could not be completely compared to finding an object or making a simple observation, as dissecting as well as some experimental practices were also involved. Heterogeneous practices thus coexisted within collecting in anatomy and pathology. Epistemological as well as pragmatic tensions arose. On top of Kohler’s framework, I introduce Sabina Leonelli’s concept of “data journey” to offer a narrative of the diversity of collecting practices involved in the Société Anatomique de Paris and the Musée Dupuytren. I use the concept to analyse how this diversity of practices impacted knowledge production. (shrink)

Although databases have been well-defined and thoroughly discussed in the computer science literature, the actual users of databases often have varying definitions and expectations of this essential computational infrastructure. Systems administrators and computer science textbooks may expect databases to be instantiated in a small number of technologies, but there are numerous examples of databases in non-conventional or unexpected technologies, such as spreadsheets or other assemblages of files linked through code. Consequently, we ask: How do the materialities of non-conventional databases differ (...) from or align with the materialities of conventional relational systems? What properties of the database do the creators of these artifacts invoke in their rhetoric describing these systems—or in the data models underlying these digital objects? To answer these questions, we conducted a close analysis of four non-conventional scientific databases. By examining the materialities of information representation in each case, we show how scholarly communication regimes shape database materialities—and how information organization paradigms shape scholarly communication. These cases show abandonment of certain constraints of relational database construction alongside maintenance of some key relational data organization strategies. We discuss the implications that these relational data paradigms have for data use, preservation, and sharing, and discuss the need to support a plurality of data practices and paradigms. (shrink)

This article examines adaptive resource management as it has been applied to the US horseshoe crab fishery over the past decade. As a critical yet constructive exercise, I have three goals: to suggest how adaptive management, for all its promise, can still be improved; to add a nuanced case study to the literatures on the quantification of nature and environmental decision-making; and to use the example of ARM to make certain temporal aspects of contemporary natural resource management more salient to (...) science and technology studies scholars—that is, to show the ways in which time matters in environmental science, policy, and the analysis thereof. I draw attention to the time-related aspects of adaptive management by developing the notions of temporal orientation and chronological accountability. Temporal orientation refers to the time-based perspectives and epistemological commitments—that is, past-facing empiricism versus future-oriented modeling—that scientists of different types bring to bear on environmental problems. Chronological accountability refers to the missing link in adaptive forms of environmental governance: firm time lines and commitments to reflexively revisit management decisions. The time-related aspects of natural resource management deserve greater attention among both environmental managers and analysts of environmental policy. (shrink)

A general view in philosophy of science says that the appropriateness of an object to act as a surrogate depends on the user’s decision to utilize it as such. This paper challenges this claim by examining the role of surrogative reasoning in high-throughput sequencing technologies as they are used in contemporary microbiome science. Drawing on this, we argue that, in technology-driven surrogates, knowledge about the type of inference practically permitted and epistemically justified by the surrogate constrains their use and thus (...) puts a limit to the user’s intentions to use any object as a surrogate for what they please. Ignoring this leads to a serious epistemic misalignment, which ultimately prevents surrogative reasoning. Thus, we conclude that knowledge about the type of surrogate reasoning that the technologies being used allow is fundamental to avoid misinterpreting the consequences of the data obtained with them, the hypothesis this data supports, and what these technologies are surrogates of. (shrink)

Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The more recent (...) modeling-based accounts still perpetuate a theory-centric view of scientific concepts, which motivated philosophers’ misplaced skepticism in the first place. (shrink)

The fossil record is paleontology’s great resource, telling us virtually everything we know about the past history of life. This record, which has been accumulating since the beginning of paleontology as a professional discipline in the early nineteenth century, is a collection of objects. The fossil record exists literally, in the specimen drawers where fossils are kept, and figuratively, in the illustrations and records of fossils compiled in paleontological atlases and compendia. However, as has become increasingly clear since the later (...) twentieth century, the fossil record is also a record of data. Paleontologists now routinely abstract information from the physical fossil record to construct databases that serve as the basis for quantitative analysis of patterns in the history of life. What is the significance of this distinction? While it is often assumed that the orientation towards treating the fossil record as a record of data is an innovation of the computer age, it turns out that nineteenth century paleontology was substantially “data driven.” This paper traces the evolution of data practices and analyses in paleontology, primarily through examination of the compendia in which the fossil record has been recorded over the past 200 years. I argue that the transition towards conceptualizing the fossil record as a record of data began long before the emergence of the technologies associated with modern databases (such as digital computers and modern statistical methods). I will also argue that this history reveals how new forms of visual representation were associated with the transition from seeing the fossil record as a record of objects to one of data or information, which allowed paleontologists to make new visual arguments about their data. While these practices and techniques have become increasingly sophisticated in recent decades, I will show that their basic methodology was in place over a century ago, and that, in a sense, paleontology has always been a “data driven” science. (shrink)

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 487-498, September 2022.

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 487-498, September 2022.

This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, (...) history, economy and society. It is argued that: Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology. (shrink)

The Bermuda Principles for DNA sequence data sharing are an enduring legacy of the Human Genome Project. They were adopted by the HGP at a strategy meeting in Bermuda in February of 1996 and implemented in formal policies by early 1998, mandating daily release of HGP-funded DNA sequences into the public domain. The idea of daily sharing, we argue, emanated directly from strategies for large, goal-directed molecular biology projects first tested within the “community” of C. elegans researchers, and were introduced (...) and defended for the HGP by the nematode biologists John Sulston and Robert Waterston. In the C. elegans community, and subsequently in the HGP, daily sharing served the pragmatic goals of quality control and project coordination. Yet in the HGP human genome, we also argue, the Bermuda Principles addressed concerns about gene patents impeding scientific advancement, and were aspirational and flexible in implementation and justification. They endured as an archetype for how rapid data sharing could be realized and rationalized, and permitted adaptation to the needs of various scientific communities. Yet in addition to the support of Sulston and Waterston, their adoption also depended on the clout of administrators at the US National Institutes of Health and the UK nonprofit charity the Wellcome Trust, which together funded 90% of the HGP human sequencing effort. The other nations wishing to remain in the HGP consortium had to accommodate to the Bermuda Principles, requiring exceptions from incompatible existing or pending data access policies for publicly funded research in Germany, Japan, and France. We begin this story in 1963, with the biologist Sydney Brenner’s proposal for a nematode research program at the Laboratory of Molecular Biology at the University of Cambridge. We continue through 2003, with the completion of the HGP human reference genome, and conclude with observations about policy and the historiography of molecular biology. (shrink)

“Ancient DNA Research” is the practice of extracting, sequencing, and analyzing degraded DNA from dead organisms that are hundreds to thousands of years old. Today, many researchers are interested in adapting state-of-the-art molecular biological techniques and high-throughput sequencing technologies to optimize the recovery of DNA from fossils, then use it for studying evolutionary history. However, the recovery of DNA from fossils has also fueled the idea of resurrecting extinct species, especially as its emergence corresponded with the book and movie Jurassic (...) Park in the 1990s. In this paper, I use historical material, interviews with scientists, and philosophical literature to argue that the search for DNA from fossils can be characterized as a data-driven and celebrity-driven practice. Philosophers have recently argued the need to seriously consider the role of data-driven inquiry in the sciences, and likewise, this history highlights the need to seriously consider the role of celebrity in shaping the kind of research that gets pursued, funded, and ultimately completed. On this point, this history highlights that the traditional philosophical and scientific distinctions between data-driven and hypothesis-driven research are not always useful for understanding the process and practice of science. Consequently, I argue that the celebrity status of a particular research practice can be considered as a “serious epistemic strategy” that researchers, as well as editors and funders, employ when making choices about their research and publication processes. This interplay between celebrity and methodology matters for the epistemology of science. (shrink)

This paper uses several case studies to suggest that (1) two prominent definitions of data do not on their own capture how scientists use data and (2) a novel perspectival account of data is needed. It then outlines some key features of what this account could look like. Those prominent views, the relational and representational, do not fully capture what data are and how they function in science. The representational view is insensitive to the scientific context in which data are (...) used. The relational account does not fully account for the empirical nature of data and how it is possible for data to be evidentially useful. The perspectival account surmounts these problems by accommodating a representational element to data. At the same time, data depend upon the epistemic context because they are the product of situated and informed judgements. (shrink)

Recent studies of scholarly data work argue that whatever researchers handle as data and, in particular, what researchers consider as potential evidence for supporting claims, counts as data. In this article I extend the relational approach towards data to the various ways of dealing with data in the course of a single research project. Relying on an example from ecology, I argue that data gain presence for and occupy researchers in manifold ways: for example, as a promise, desire or pressure, (...) or as a problem of trust and strength. In this way we notice that data, in the eyes of researchers, have more than one mode of existence, each of which is linked with its own expectations, challenges and actions. And we notice that these modes of existence not only coexist in the framework of a single project, but can also compete with each other. (shrink)

ZusammenfassungGenomdaten, Kernstück der 2008 ausgerufenen Big Data-Revolution der Biologie, werden voll automatisiert sequenziert und analysiert. Der Wechsel von der manuellen Laborpraktik der Elektrophorese-Sequenzierung zu DNA-Sequenziermaschinen und softwarebasierten Analyseprogrammen vollzog sich zwischen 1982 und 1992. Erst dieser Wechsel ermöglichte die Flut an Daten, die mit der zweiten und dritten Generation der DNA-Sequenzierer erheblich zunimmt. Doch mit diesem Wechsel verändern sich auch die Validierungsstrategien der Genomdaten. Der Beitrag untersucht beides – die Automatisierung und die damit verbundene Validierungskultur – um ein Bild der (...) Komplexität der Datengenerierung und deren Datenpositivismus zu geben. Leitend ist dabei die Frage, ob dieser Datenpositivismus die Grundlage der aktuell angekündigten Big Data-Revolution der Molekularbiologie ist oder deren Datenhybris. (shrink)

ZusammenfassungGenomdaten, Kernstück der 2008 ausgerufenen Big Data-Revolution der Biologie, werden voll automatisiert sequenziert und analysiert. Der Wechsel von der manuellen Laborpraktik der Elektrophorese-Sequenzierung zu DNA-Sequenziermaschinen und softwarebasierten Analyseprogrammen vollzog sich zwischen 1982 und 1992. Erst dieser Wechsel ermöglichte die Flut an Daten, die mit der zweiten und dritten Generation der DNA-Sequenzierer erheblich zunimmt. Doch mit diesem Wechsel verändern sich auch die Validierungsstrategien der Genomdaten. Der Beitrag untersucht beides – die Automatisierung und die damit verbundene Validierungskultur – um ein Bild der (...) Komplexität der Datengenerierung und deren Datenpositivismus zu geben. Leitend ist dabei die Frage, ob dieser Datenpositivismus die Grundlage der aktuell angekündigten Big Data-Revolution der Molekularbiologie ist oder deren Datenhybris. (shrink)

In its last round of publications in September 2012, the Encyclopedia Of DNA Elements (ENCODE) assigned a biochemical function to most of the human genome, which was taken up by the media as meaning the end of ‘Junk DNA’. This provoked a heated reaction from evolutionary biologists, who among other things claimed that ENCODE adopted a wrong and much too inclusive notion of function, making its dismissal of junk DNA merely rhetorical. We argue that this criticism rests on misunderstandings concerning (...) the nature of the ENCODE project, the relevant notion of function and the claim that most of our genome is junk. We argue that evolutionary accounts of function presuppose functions as ‘causal roles’, and that selection is but a useful proxy for relevant functions, which might well be unsuitable to biomedical research. Taking a closer look at the discovery process in which ENCODE participates, we argue that ENCODE’s strategy of biochemical signatures successfully identified activities of DNA elements with an eye towards causal roles of interest to biomedical research. We argue that ENCODE’s controversial claim of functionality should be interpreted as saying that 80 % of the genome is engaging in relevant biochemical activities and is very likely to have a causal role in phenomena deemed relevant to biomedical research. Finally, we discuss ambiguities in the meaning of junk DNA and in one of the main arguments raised for its prevalence, and we evaluate the impact of ENCODE’s results on the claim that most of our genome is junk. (shrink)

Data-intensive science comes with increased risks concerning quality and reliability of data, and while trust in science has traditionally been framed as a matter of scientists being expected to adhere to certain technical and moral norms for behaviour, emerging discourses of open science present openness and transparency as substitutes for established trust mechanisms. By ensuring access to all available information, quality becomes a matter of informed judgement by the users, and trust no longer seems necessary. This strategy does not, however, (...) take into consideration the networks of professionals already enabling data-intensive science by providing high-quality data. In the life sciences, biological data- and knowledge bases managed by expert biocurators have become crucial for data-intensive research. In this paper, I will use the case of biocurators to argue that openness and transparency will not diminish the need for trust in data-intensive science. On the contrary, data-intensive science requires a reconfiguration of existing trust mechanisms in order to include those who take care of and manage scientific data after its production. (shrink)

This paper is a critical assessment of the epistemological impact of the systematic quantification of nature with the accumulation of big datasets on the practice and orientation of ecological science. We examine the contents of big databases and argue that it is not just accumulated information; records are translated into digital data in a process that changes their meanings. In order to better understand what is at stake in the ‘datafication’ process, we explore the context for the emergence and quantification (...) of biodiversity in the 1980s, along with the concept of the global environment. In tracing the origin and development of the global biodiversity information facility we describe big data biodiversity projects as a techno-political construction dedicated to monitoring a new object: the global diversity. We argue that, biodiversity big data became a powerful driver behind the invention of the concept of the global environment, and a way to embed ecological science in the political agenda. (shrink)

1. Overview and organizing themes 2. Historical Review: Aristotle to Mill 3. Logic of method and critical responses 3.1 Logical constructionism and Operationalism 3.2. H-D as a logic of confirmation 3.3. Popper and falsificationism 3.4 Meta-methodology and the end of method 4. Statistical methods for hypothesis testing 5. Method in Practice 5.1 Creative and exploratory practices 5.2 Computer methods and the ‘third way’ of doing science 6. Discourse on scientific method 6.1 “The scientific method” in science education and as seen (...) by scientists 6.2 Privileged methods and ‘gold standards’ 6.3 Scientific method in the court room 6.4 Deviating practices 7. Conclusion Bibliography Academic Tools Other Internet Resources Related Entries . (shrink)