372 pages | 31 B/W Illus.
Visual representations (photographs, diagrams, etc.) play crucial roles in scientific processes. They help, for example, to communicate research results and hypotheses to scientific peers as well as to the lay audience. In genuine research activities they are used as evidence or as surrogates for research objects which are otherwise cognitively inaccessible. Despite their important functional roles in scientific practices, philosophers of science have more or less neglected visual representations in their analyses of epistemic methods and tools of reasoning in science. This book is meant to fill this gap. It presents a detailed investigation into central conceptual issues and into the epistemology of visual representations in science.
Chapter 4 of this book are freely available as downloadable Open Access PDFs under a CC-BY 3.0 license. https://s3-us-west-2.amazonaws.com/tandfbis/rt-files/docs/Open+Access+Chapters/9781138089938_CCBYoachapter4.pdf
List of Illustrations
1.1 Topics and Methodology
2 What Are Scientific Visualisations?
2.1 Characteristics of Visual Representations in Science
2.1.2 Imaging Techniques
2.1.3 Data Visualisations
2.1.5 Interim Results: what Can Be Learnt from Paradigmatic Instances?
2.2 The Nature of Depiction
2.2.1 Resemblance Theories
2.2.3 Experience-based Theories
2.2.4 Recognition Theories
2.2.5 Mixed Theories and Image Science
2.2.6 Interim Results: what Can Be Learnt from Picture Theory?
2.3 Summary: Correlations Between Categories and Theories?
3 Functional Roles, Appearances and the Problem of Diversity
3.1 Context-orientated Approach
3.1.1 Exploratory vs. Explanatory Use
3.1.2 Context-related Problems
3.1.3 Reasons (I) – Causality and Informativeness
3.1.4 Reasons (II) – Trust and Reputation
3.1.5 Interim Results: what Can Be Learnt about Reasons?
3.2 A Social Explanation of Diversity
3.2.1 Preliminaries on Ludwik Fleck
3.2.2 Scientific Communication – Aims and Modes
3.2.3 Visual Representations as Proper Parts of Scientific Communication
3.2.4 Interim Results: what Can Be Learnt from Social Mechanisms?
4 The Epistemic Status of Scientific Visualisations
4.1 Visual Arguments?
4.1.1 The Philosophical Challenge
4.1.2 Laura Perini on Visual Representations in Scientific Arguments
4.1.3 Giving Reasons, Drawing Conclusions
4.1.4 Interim Results: what Can Be Learnt from Argumentation Theory?
4.2 The Cognitive Content of Visual Representations
4.2.1 Content Translatability and the Reducibility-Thesis
4.2.2 Perception and Non-propositional Content
4.2.3 Evolutionary Merits of Perception
4.2.4 Interim Results: what Can Be Learnt from Theories of Perception?
4.3 The Cognitive Value of Visualisations
4.3.1 Educational Psychology
4.3.2 Visual Representations and the Varieties of Knowledge
4.3.3 Visual Representations and Scientific Understanding
4.3.4 Interim Results: scientific Images as a Source of Knowledge and Understanding
5 Outlook: New Responsibilities?
Even though technoscientific research is as old as alchemy and pharmacy, agricultural research and synthetic chemistry, philosophers of science had little to say about it until recently. This book series is the first to explicitly accept the challenge to study not just technical aspects of theory development and hypothesis testing but the specific ways in which knowledge is produced in a technological setting. When one seeks to achieve basic capabilities of manipulation, visualization, or predictive control, how are problems defined and research fields established, what kinds of explanations are sought, how are findings validated, what are the contributions of different kinds of expertise, how do epistemic and social values enter into the research process? And most importantly for civic observers of contemporary research: how is robustness and reliability achieved even in the absence of complete scientific understanding?
Editorial Board: Hanne Andersen (University of Copenhagen), Bernadette Bensaude-Vincent (University of Paris, Sorbonne), Martin Carrier (University of Bielefeld), Graeme Gooday (University of Leeds), Don Howard (University of Notre Dame), Ann Johnson (Cornell University), Cyrus Mody (Maastricht University), Maureen O'Malley (University of Sydney), Roger Strand (University of Bergen), Nancy Tuana (Pennsylvania State University).
Read Chapter 4 - Open Access. Open Access content has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives license.