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In recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemp...
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 variet...
The standard teaching text for Data and Society modules explaining to undergraduates, in different social-science disciplines, the Big Data Revolution in an accessible and critical way.
To most scientists, and to those interested in the sciences, understanding is the ultimate aim of scientific endeavor. In spite of this, understanding, and how it is achieved, has received little attention in recent philosophy of science. Scientific Understanding seeks to reverse this trend by providing original and in-depth accounts of the concept of understanding and its essential role in the scientific process. To this end, the chapters in this volume explore and develop three key topics: understanding and explanation, understanding and models, and understanding in scientific practice. Earlier philosophers, such as Carl Hempel, dismissed understanding as subjective and pragmatic. They bel...
This Element presents a philosophical exploration of the concept of the 'model organism' in contemporary biology. Thinking about model organisms enables us to examine how living organisms have been brought into the laboratory and used to gain a better understanding of biology, and to explore the research practices, commitments, and norms underlying this understanding. We contend that model organisms are key components of a distinctive way of doing research. We focus on what makes model organisms an important type of model, and how the use of these models has shaped biological knowledge, including how model organisms represent, how they are used as tools for intervention, and how the representational commitments linked to their use as models affect the research practices associated with them. This title is available as Open Access on Cambridge Core.
Selling science has become a common practice in contemporary universities. This commodification of academia pervades many aspects of higher education, including research, teaching, and administration. As such, it raises significant philosophical, political, and moral challenges. This volume offers the first book-length analysis of this disturbing trend from a philosophical perspective and presents views by scholars of philosophy of science, social and political philosophy, and research ethics. The epistemic and moral responsibilities of universities, whether for-profit or nonprofit, are examined from several philosophical standpoints. The contributors discuss the pertinent epistemological an...
Interdisciplinary perspectives on cultural evolution that reject meme theory in favor of a complex understanding of dynamic change over time How do cultures change? In recent decades, the concept of the meme, posited as a basic unit of culture analogous to the gene, has been central to debates about cultural transformation. Despite the appeal of meme theory, its simplification of complex interactions and other inadequacies as an explanatory framework raise more questions about cultural evolution than it answers. In Beyond the Meme, William C. Wimsatt and Alan C. Love assemble interdisciplinary perspectives on cultural evolution, providing a nuanced understanding of it as a process in which d...
Ten years after the Human Genome Project’s completion the life sciences stand in a moment of uncertainty, transition, and contestation. The postgenomic era has seen rapid shifts in research methodology, funding, scientific labor, and disciplinary structures. Postgenomics is transforming our understanding of disease and health, our environment, and the categories of race, class, and gender. At the same time, the gene retains its centrality and power in biological and popular discourse. The contributors to Postgenomics analyze these ruptures and continuities and place them in historical, social, and political context. Postgenomics, they argue, forces a rethinking of the genome itself, and opens new territory for conversations between the social sciences, humanities, and life sciences. Contributors. Russ Altman, Rachel A. Ankeny, Catherine Bliss, John Dupré, Michael Fortun, Evelyn Fox Keller, Sabina Leonelli, Adrian Mackenzie, Margot Moinester, Aaron Panofsky, Sarah S. Richardson, Sara Shostak, Hallam Stevens
Interdisciplinarity has become a buzzword in academia, as research universities funnel their financial resources toward collaborations between faculty in different disciplines. In theory, interdisciplinary collaboration breaks down artificial divisions between different departments, allowing more innovative and sophisticated research to flourish. But does it actually work this way in practice? Investigating Interdisciplinary Collaboration puts the common beliefs about such research to the test, using empirical data gathered by scholars from the United States, Canada, and Great Britain. The book’s contributors critically interrogate the assumptions underlying the fervor for interdisciplinarity. Their attentive scholarship reveals how, for all its potential benefits, interdisciplinary collaboration is neither immune to academia’s status hierarchies, nor a simple antidote to the alleged shortcomings of disciplinary study. Chapter 10 is available Open Access here (https://www.ncbi.nlm.nih.gov/books/NBK395883)
Data-intensive science has the potential to transform scientific research and quickly translate scientific progress into complete solutions, policies, and economic success. But this collaborative science is still lacking the effective access and exchange of knowledge among scientists, researchers, and policy makers across a range of disciplines. Bringing together leaders from multiple scientific disciplines, Data-Intensive Science shows how a comprehensive integration of various techniques and technological advances can effectively harness the vast amount of data being generated and significantly accelerate scientific progress to address some of the world's most challenging problems. In the ...