Patient-derived xenografts are currently promoted as new translational models in precision oncology. PDXs are immunodeficient mice with human tumors that are used as surrogate models to represent specific types of cancer. By accounting for the genetic heterogeneity of cancer tumors, PDXs are hoped to provide more clinically relevant results in preclinical research. Further, in the function of so-called “mouse avatars”, PDXs are hoped to allow for patient-specific drug testing in real-time. This paper examines the circulation of knowledge and bodily material (...) across the species boundary of human and personalized mouse model, historically as well as in contemporary practices. PDXs raise interesting questions about the relation between animal model and human patient, and about the capacity of hybrid or interspecies models to close existing translational gaps. We highlight that the translational potential of PDXs not only depends on representational matching of model and target, but also on temporal alignment between model development and practical uses. Aside from the importance of ensuring temporal stability of human tumors in a murine body, the mouse avatar concept rests on the possibility of aligning the temporal horizons of the clinic and the lab. We examine strategies to address temporal challenges, including cryopreservation and biobanking, as well as attempts to speed up translation through modification and use of faster developing organisms. We discuss how featured model virtues change with precision oncology, and contend that temporality is a model feature that deserves more philosophical attention. (shrink)

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value of (...) discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

Debate about the epistemic prowess of historical science has focused on local underdetermination problems generated by a lack of historical data; the prevalence of information loss over geological time, and the capacities of scientists to mitigate it. Drawing on Leonelli’s recent distinction between ‘phenomena-time’ and ‘data-time’ I argue that factors like data generation, curation and management significantly complexifies and undermines this: underdetermination is a bad way of framing the challenges historical scientists face. In doing so, I identify circumstances of epistemic (...) scarcity where underdetermination problems are particularly salient, and discuss cases where legacy data—data generated using differing technologies and systems of practice—are drawn upon to overcome underdetermination. This suggests that one source of overcoming underdetermination is our knowledge of science’s past. Further, data-time makes agnostic positions about the epistemic fortunes of scientists working under epistemic scarcity more plausible. But agnosticism seems to leave philosophers without much normative grip. So, I sketch an alternative approach: focusing on the strategies scientists adopt to maximize their epistemic power in light of the resources available to them. (shrink)

This article investigates epistemological aspects of scientists’ reuse of empirical data over decades and centuries. Giving examples, I discuss three respects in which empirical data are historical entities and the implications for the notion of data reuse. First, any data reuse necessitates metadata, which specify the data’s circumstances of origin. Second, interpretation of historical data often requires the tools of humanities disciplines, which produce a further historicization of data. Finally, some qualitative social scientists hold that data are personal to the (...) researcher who coconstructs them in the research process and are therefore skeptical about the prospects of reusing data. (shrink)

Philosophers of science are well aware that theories are underdetermined by data. But what about the data? Scientific data are selected and processed representations or pieces of nature. What is useless context and what is valuable specimen, as well as how specimens are processed for study, are not obvious or predetermined givens. Instead, they are decisions made by scientists and other research workers, such as technicians, that produce different outcomes for the data. Vertebrate fossils provide a revealing case of this (...) data-processing, because they are embedded in rock that often matches the fossils’ color and texture, requiring an expert eye to judge where the fossil/context interface is. Fossil preparators then permanently define this interface by chiseling away the material they identify as rock. As a result, fossil specimens can emerge in multiple possible forms depending on the preparator’s judgment, skill, and chosen tools. A prepared fossil then is not yet data but potential data, following Leonelli’s relational framework in which data are defined as evidence that scientists have used to support a proposed theory. This paper draws on ethnographic evidence to assess how scientists overcome this underdetermination of specimens, as potential data, in addition to the underdetermination of theories and of data, to successfully construct specimen-based knowledge. Among other strategies, paleontology maintains a division of labor between data-makers and theory-makers. This distinction serves to justify the omission of preparators’ nonstandard, individualized techniques from scientific publications. This separation has benefits for both scientists and technicians; however, it restricts knowledge production by preventing scientists from understanding how the pieces of nature they study were processed into researchable specimens. (shrink)

This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in (...) making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research. (shrink)

I offer four ways of distinguishing paleobiology from neontology, and from this develop a sketch of the philosophy of paleobiology. I then situate and describe the papers in the special issue Paleobiology and Philosophy, and reflect on the value and prospects of paleontology-focused philosophy.