Scientific Visualisation: Epistemic Weight and Surpluses

Description

Much of the recent confidence in the future of science and technology stems from advances in scientific visualisation. But is it right to assume that visual – and especially pictorial – measures carry special epistemic weight in the context of scientific reasoning? Do pictorial approaches have any surpluses, compared to other semiotic types? This book delves into these issues from the point of view of the philosophy of science. New examples from the field of scientific visualisation are introduced in order to account for the epistemic weight and surpluses of syntactically dense – pictorial – symbol systems. Cover Table of Contents Abbreviations and Acronyms Table of Figures List of Tables Preface I Introduction II Picture-like Means in Science 2.1 ‘Figure’ – ‘Image’ – ‘Picture’ 2.1.1 Extended definition 2.1.2 Specifications 2.1.2.1 History-based specification 2.1.2.2 Case-based specification 2.1.2.3 Exclusive concept-based specification 2.1.2.4 Inclusive concept-based specification 2.1.3 Lessons learned 2.2 An epistemic account of picture-like means 2.2.1 Epistemic problems 2.2.1.1 Defining ‘epistemic’ 2.2.1.2 Analysing ‘function’ and functions 2.2.1.3 Desiderata: epistemic weight and epistemic surpluses 2.2.2 Figures and picture-likeness 2.2.2.1 What are scientific figures? 2.2.2.2 What makes scientific figures ‘picture-like’? 2.3 Picture-like means in science as a philosophical problem 2.3.1 The failure of the purely linguistic view of representation 2.3.2 The role of picture-like means in recent accounts of science 2.3.3 Techno-science and the emergence of scientific visualisation III Examples 3.1 Example 1: modelling mesenchymal stem cell differentiation 3.1.1 Research objectives 3.1.2 Motivators 3.1.3 Initial assumptions (a) 3.1.4 Initial assumptions (b) 3.1.5 Model 3.1.6 Stability properties 3.1.7 Bifurcation properties 3.1.8 Single cell switching 3.1.9 Cell population effects 3.1.10 Discussion 3.2 Example 2: modelling signal transduction in mammal cells 3.2.1 Research objectives and motivators 3.2.2 Related work 3.2.3 Techniques combined 3.2.4 Schematic illustration of the cell model 3.2.5 Rendering scheme for proteins and trajectories 3.2.6 Rendering scheme for reactions 3.2.7 Tractability measures: cuts and transections 3.2.8 Tractability measures: depth cues 3.2.9 Alternative rendering: microscopy-like images 3.2.10 Application I: transduction types for MAPK 3.2.11 Application II: delivery of drug molecules 3.2.12 Technical aspects 3.2.13 Results 3.2.14 Conclusion and future work 3.3 Abstractions 3.3.1 Functional involvement of figures 3.3.2 Practical implications of figure-likeness 3.3.3 Methodological relevance of figures 3.3.4 Compositional and representational aspects of figures 3.3.5 Observations on the prevalence of figures IV Epistemic Weight and Epistemic Surpluses 4.1 Recent accounts of picture-like means in science 4.1.1 Operational accounts: analysing modes of implementation 4.1.2 Ontological accounts: analysing traits of occurrence or identification 4.1.3 Functional accounts: analysing practical embeddings 4.1.4 Interim summary 4.2 An extended argument for the epistemic weight of picture-like means 4.2.1 The role of picture-like means 4.2.1.1 Picture-like means as arguments 4.2.1.2 Picture-like means in mere support of arguments 4.2.1.3 Picture-like means in arguments 4.2.2 Picture-likeness revisited 4.2.2.1 Learning from misconceptions 4.2.2.2 From referential systems towards symbol systems 4.2.2.3 What is a symbol system? 4.2.2.4 What makes a symbol system picture-like? 4.2.3 A case for the epistemic weight of picture-like means 4.2.4 Perini’s account: problems and gaps 4.2.5 A case for the epistemic weight of syntactically dense systems 4.2.5.1 Continuous vs. strict dichotomies 4.2.5.2 The concept of ad hoc syntaxes 4.2.5.3 Explanatory potential 4.2.5.4 Ad hoc syntaxes in formal systems 4.2.5.5 Differences to other approaches 4.3 A new account of the epistemic surpluses of picture-like means 4.3.1 Issues with defining epistemic surpluses 4.3.2 Deficiency arguments 4.3.2.1 Some ambiguities about ambiguity issues 4.3.2.2 On the (im-)possibility of formalising pictorial systems 4.3.3 Efficiency arguments 4.3.3.1 The new master argument: spatial efficiency 4.3.3.2 Internalised codes and the haunting intuition about similarity 4.3.3.3 Refining the notion of interaction V Outlook Summary (English) Summary (German) Literature