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Data-Centric Biology
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...
Data Journeys in the Sciences
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...
Data and Society
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.
Scientific Understanding
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...
Model Organisms
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.
The Commodification of Academic Research
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...
Data-Centric Biology
Over the last two decades, digital access to data has revolutionized research methods and ways of doing science in the biological and biomedical fields. Prominent scientists have characterized this shift as leading to a new, data-intensive paradigm for research, encompassing innovative ways to produce, store, disseminate, and interpret huge masses of data. In this book Sabina Leonelli explores the epistemological challenges this poses to how life is researched and understood. By following how data travels across research contexts, and the role played by standards, theories, models, and human agency in shaping their evidential value, she shows the conditions under which digitally available data further our understanding of life. Turning to how the characteristics of data-intensive science bear on philosophical debates, Leonelli explores the shifting criteria for what counts as scientific evidence and how data are transformed into new knowledge. In short, she argues that a philosophical characterization of how data and knowledge move from one context to another is of fundamental importance to a productive philosophical understanding of contemporary scientific practices."
Beyond the Meme
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...
Collecting Experiments
Databases have revolutionized nearly every aspect of our lives. Information of all sorts is being collected on a massive scale, from Google to Facebook and well beyond. But as the amount of information in databases explodes, we are forced to reassess our ideas about what knowledge is, how it is produced, to whom it belongs, and who can be credited for producing it. Every scientist working today draws on databases to produce scientific knowledge. Databases have become more common than microscopes, voltmeters, and test tubes, and the increasing amount of data has led to major changes in research practices and profound reflections on the proper professional roles of data producers, collectors, ...
Data-Intensive Science
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 ...
