Pictorial representations such as diagrams and figures are widely used in scientific literature for explanatory and descriptive purposes. The intuitive nature of pictorial representations coupled with texts foster a better understanding of the objects of study. Biological mechanisms and processes can be clearly illustrated and grasped in pictures. I argue that pictorial representations describe biological phenomena by telling stories. I elaborate on the role of narrative structures of pictures in the frontier research using a case study in immunology. I articulate (...) that pictures with an inherent narrative structure are crucial in biological sciences. (shrink)

For centuries, philosophers of time have produced texts containing words and pictures. Although some historians study visual representations of time, I have not found any history of philosophy on pictures of time within texts. This paper argues that studying such pictures can be rewarding. I will make this case by studying pictures of time in the works of Leibniz, Arthur Eddington and C. D. Broad, and argue they play subtle roles. Further, I will argue that historians of philosophy more widely (...) could benefit from paying more attention to pictures. (shrink)

For centuries, philosophers of time have produced texts containing words and pictures. Although some historians study visual representations of time, I have not found any history of philosophy on pictures of time within texts. This paper argues that studying such pictures can be rewarding. I will make this case by studying pictures of time in the works of Leibniz, Arthur Eddington and C. D. Broad, and argue they play subtle roles. Further, I will argue that historians of philosophy more widely (...) could benefit from paying more attention to pictures. (shrink)

An important function of scientific diagrams is to identify causal relationships. This commonly relies on contrasts that highlight the effects of specific difference-makers. However, causal contrast diagrams are not an obvious and easy to recognize category because they appear in many guises. In this paper, four case studies are presented to examine how causal contrast diagrams appear in a wide range of scientific reports, from experimental to observational and even purely theoretical studies. It is shown that causal contrasts can be (...) expressed in starkly different formats, including photographs of complexly visualized macromolecules as well as line graphs, bar graphs, or plots of state spaces. Despite surface differences, however, there is a measure of conceptual unity among such diagrams. In empirical studies they generally serve not only to infer and communicate specific causal claims, but also as evidence for them. The key data of some studies is given nowhere except in the diagrams. Many diagrams show multiple causal contrasts in order to demonstrate both that an effect exists and that the effect is specific -- that is, to narrowly circumscribe the phenomenon to be explained. In a large range of scientific reports, causal contrast diagrams reflect the core epistemic claims of the researchers. (shrink)

Art and science is an area of research that has strengthened recently, mainly due to the impact of interdisciplinary work. At the same time, approaches between the humanities and the sciences have succeeded in re-signifying traditional views towards critical positions such as postcolonialism, especially in the colonially so-called “Global South”. In this paper, we want to review the case of the work of the Mexican artist Octavio Ocampo through works that present the case of biological and cultural evolution. From this, (...) we want to reflect on the public perception of science in Mexico, the tensions between social and natural sciences, and the urgent need to strengthen the postcolonial discourse in scientific practice. (shrink)

One way visual representations might function in scientific reasoning is to convey content that is true or false, analogous to making a claim. An alternative way that visual representations might function is as an object that may make statements true or false, but is not itself true or false, analogous to a scientific model. In this paper I evaluate the most recent and extended defense of this latter position and show that the case study involved does not in fact support (...) the view that the diagrams discussed function as truth-makers rather than truth bearers. (shrink)

We can witness the recent surge of interest in the interaction between cognitive science, philosophy of science, and aesthetics on the problem of representation. This naturally leads us to rethinking the achievements of Goodman’s monumental book Languages of Art. For, there is no doubt that no one else contributed more than Goodman to throw a light on the cognitive function of art. Ironically, it could be also Goodman who has been the stumbling block for a unified theory of representation. In (...) this paper, I shall contrast the ways how differently misrepresentation has been treated in cognitive science, aesthetics, and philosophy of science. And I shall show that it is Goodman’s unnecessary separation of resemblance and representation in art that made such a difference. As a conclusion, I will indicate some of the most promising projects toward the unified theory of representation the revolt against Goodman’s rejection of resemblance theories might promise to us. (shrink)

In this essay, I first consider a popular view of models and modeling, the similarity view. Second, I contend that arguments for it fail and it suffers from what I call “Hughes’ worry.” Third, I offer a deflationary approach to models and modeling that avoids Hughes’ worry and shows how scientific representations are of apiece with other types of representations. Finally, I consider an objection that the similarity view can deal with approximations better than the deflationary view and show that (...) this is not so. (shrink)

Scientists use visualisations of different kinds in a variety of ways in their scientific work. In the following article, we will take a closer look at the use of photographic pictures as scientific evidence. In accordance with Patrick Maynard’s thesis, photography will be regarded as a family of technologies serving different purposes in divergent contexts. One of these is its ability to detect certain phenomena. Nonetheless, with regard to the philosophical thesis of theory-ladenness of observation, we encounter certain reservations concerning (...) the status of photography and that of photographic pictures in the process of measurement in science. Accordingly, the aim of this paper is twofold: We will discuss suggested solutions both for the technological and for the psychological part of the problem of theory-ladenness appearing in the context of the use of photography in scientific observations. The essential proposal will be to follow Christian Suhm in his advice to make a distinction between theory-relativity and theory-ladenness. (shrink)

There are two distinct interpretations of the role that Feynman diagrams play in physics: (i) they are calculational devices, a type of notation designed to keep track of complicated mathematical expressions; and (ii) they are representational devices, a type of picture. I argue that Feynman diagrams not only have a calculational function but also represent: they are in some sense pictures. I defend my view through addressing two objections and in so doing I offer an account of representation that explains (...) why Feynman diagrams represent. The account that I advocate is a version of that defended by Kendall Walton, which provides us with a basic characterization of the way that representations in general work and is particularly useful for understanding distinctively pictorial representations - in Walton's terms, depictions. The question of the epistemic function of Feynman diagrams as pictorial representations is left for another time. (shrink)

Meynell’s contention is that feminists should attend to pictures in science as distinctive bearers of epistemic content that cannot be reduced to propositions. Remarks on the practice and function of medical illustration—specifically, images Nancy Tuana used in her discussion of the construction of ignorance of women’s sexual function (2004)—show pictures to be complex and powerful epistemic devices. Their affinity with perennial feminist concerns, the relation between epistemic subject and object, and the nature of social knowledge, are of particular interest.

This paper articulates and defends three interconnected claims: first, that the debate on the role of values for science misses a crucial dimension, the institutional one; second, that institutions occupy the intermediate level between scientific activities and values and that they are to be systematically integrated into the analysis; third, that the appraisal of the institutions of science with respect to values should be undertaken within the premises of a comparative approach rather than an ideal approach. Hence, I defend the (...) view that the issue be framed in reference to the following question: "What kind of institutional rules should be in place in order for the scientific process to unfold in such a way that the values that we deem more important come to the fore?" Addressing this concern is equivalent to conducting a debate on institutions and their role for science. (shrink)

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is provided, which sheds light on explanatory (...) unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

Using as case studies two early diagrams that represent mechanisms of the cell division cycle, we aim to extend prior philosophical analyses of the roles of diagrams in scientific reasoning, and specifically their role in biological reasoning. The diagrams we discuss are, in practice, integral and indispensible elements of reasoning from experimental data about the cell division cycle to mathematical models of the cycle’s molecular mechanisms. In accordance with prior analyses, the diagrams provide functional explanations of the cell cycle and (...) facilitate the construction of mathematical models of the cell cycle. But, extending beyond those analyses, we show how diagrams facilitate the construction of mathematical models, and we argue that the diagrams permit nomological explanations of the cell cycle. We further argue that what makes diagrams integral and indispensible for explanation and model construction is their nature as locality aids: they group together information that is to be used together in a way that sentential representations do not. (shrink)

In practice, scientists must convey data in a “representational style”. Various authors seek to explain the epistemic role of scientific visual representation in terms of formal conventions. Goodman also tends to dismiss the epistemic relevance of human cognition. My position is that visual conventions are nonarbitrary, in that they play to scientists’ cognitive abilities and limitations. My account draws on Perini's formal analysis, scientific case studies, and empirical literature on global pattern detection in neurotypicals, autistics, and dyslexics.

ArgumentA growing cross-disciplinary literature has acknowledged the importance of verbal-visual interaction in the creation and communication of scientific texts. I contend that the proper understanding of these texts must flow from a hermeneutic model that takes verbal-visual interaction seriously, one that is firmly grounded in cognitive constraints and affordances. The model I propose has two modules, one for perception, derived from Gestalt psychology, the other for cognition, derived from Peirce's semiotics. I apply this model to an important but largely neglected (...) text in the history of nineteenth-century science, Charles Lyell'sThe Geological Evidences of the Antiquity of Man, and to two accounts by well-respected historians of science, both of the same key discovery in quantum physics. In doing so, I hope to demonstrate the advisability of incorporating the exegetical practices my model entails into the everyday practices of historians of science. (shrink)

Exact sciences are described as sciences whose theories are formalized. These are contrasted to inexact sciences, whose theories are not formalized. Formalization is described as a broader category than mathematization, involving any form/content distinction allowing forms, e.g., as represented in theoretical models, to be studied independently of the empirical content of a subject-matter domain. Exactness is a practice depending on the use of theories to control subject-matter domains and to align theoretical with empirical models and not merely a state of (...) a science. Inexact biological sciences tolerate a degree of “mismatch” between theoretical and empirical models and concepts. Three illustrations from biological sciences are discussed in which formalization is achieved by various means: Mendelism, Weismannism, and Darwinism. Frege’s idea of a “conceptual notation” is used to further characterize the notion of a form/content distinction. (shrink)

Organic chemists have been able to develop a robust, theoretical understanding of the phenomena they study; however, the primary theoretical devices employed in this field are not mathematical equations or laws, as is the case in most other physical sciences. Instead it is diagrams, and in particular structural formulas and potential energy diagrams, that carry the explanatory weight in the discipline. To understand how this is so, it is necessary to investigate both the nature of the diagrams employed in organic (...) chemistry and how these diagrams are used in the explanations of the discipline. I will begin this paper by characterizing some of the major ways that structural formulas used in organic chemistry. Next I will present a model of the explanations in organic chemistry and describe how both structural formulas and potential energy diagrams contribute to these explanations. This will be followed by several examples that support my abstract account of the role of diagrams in the explanations of organic chemistry. In particular, I will consider both the appeal to ‘hyperconjugation’ in the explanation of alkene stability and how the idea of ‘ring strain’ was developed to explain the relative stability of cyclic compounds. (shrink)

Organic chemistry provides fertile ground for scholars interested in understanding the role of non-linguistic representations in scientific thinking. In this discipline, it is not plausible to regard diagrams as simply heuristic aids for expressing or applying what is essentially a linguistic theory. Instead, it is more plausible to think of linguistic representation as supplementing theories whose principal expression is diagrammatic. Among the many sorts of diagrams employed by organic chemists, structural formulas are the most important. In this paper, by examining (...) two central episodes in the development of structural formulas—Kekulé’s proposal of a structure for benzene and Ingold’s explanation of dipole moments in terms of ‘mesomerism’—I investigate how the norms for the production and interpretation of structural formulas evolve in response to experimental results and theoretical developments. I conclude that one principal way in which structural formulas embody the theory of organic chemistry is through these evolving norms. (shrink)

Philosophers have traditionally conceived of discovery in terms of internal cognitive acts. Close consideration of Rosalind Franklin's role in the discovery of the DNA double helix, however, reveals some problems with this traditional conception. This article argues that defining discovery in terms of mental operations entails problematic conclusions and excludes acts that should fall within the domain of discovery. It proposes that discovery be expanded to include external acts of making visible. Doing so allows for a reevaluation of Franklin's role (...) in the discovery of the structure of DNA. (shrink)

Semantic networks were developed in cognitive science and artificial intelligence studies as graphical knowledge representation and inference tools emulating human thought processes. Formal analysis of the representation and inference capabilities of the networks modeled them as subsets of standard first-order logic (FOL), restricted in the operations allowed in order to ensure the tractability that seemed to characterize human reasoning capabilities. The graphical network representations were modeled as providing a visual language for the logic. Sub-sets of FOL targeted on knowledge representation (...) came to be called description logics, and research on these logics has focused on issues of tractability of subsets with differing representation capabilities, and on the implementation of practical inference systems achieving the best possible performance. Semantic network research has kept pace with these developments, providing visual languages for knowledge entry, editing, and presenting the results of inference, that translate unambiguously to the underlying description logics. This paper discusses the design issues for such semantic network formalisms, and illustrates them through detailed examples of significant generic knowledge structures analyzed in the literature, including determinables, contrast sets, genus/differentiae, taxonomies, faceted taxonomies, cluster concepts, family resemblances, graded concepts, frames, definitions, rules, rules with exceptions, essence and state assertions, opposites and contraries, relevance, and so on. Such examples provide important test material for any visual language formalism for logic. (shrink)

The aim of this paper is to engage with the interplay between representational content and design in chemistry and to explore some of its epistemological consequences. Constraints on representational content arising from the aspectual structure of representation can be manipulated by design. Designs are epistemologically important because representational content, hence our knowledge of target systems in chemistry, can change with design. The significance of this claim is that while it has been recognised that the way one conveys information makes a (...) difference to the inferences one can draw from representations in spite of the invariance of informational content, the present paper argues that in chemistry and biochemistry it is often the case that designs have cognitive priority relative to informational content. (shrink)

Diagrams can serve as representational models in scientific research, yet important questions remain about how they do so. I address some of these questions with a historical case study, in which diagrams were modified extensively in order to elaborate an early hypothesis of protein synthesis. The diagrams’ modelling role relied mainly on two features: diagrams were modified according to syntactic rules, which temporarily replaced physico-chemical reasoning, and diagram-to-target inferences were based on semantic interpretations. I then explore the lessons for the (...) relative roles of syntax, semantics, external marks, and mental images, for justifying diagram-to-target inferences, and for the “artefactual approach” to scientific models. (shrink)

Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right, that they depart from known forms of scientific models in significant ways, and that a proper understanding of the type of model simulations (...) are fundamental for their philosophical assessment. I argue that simulation models can be distinguished from other forms of models by the many algorithmic structures, representation relations, and new semantic connections involved in their architecture. In this article, I reconstruct a general architecture for a simulation model, one that faithfully captures the complexities involved in most scientific research with computer simulations. Furthermore, I submit that a new methodology capable of conforming such architecture into a fully functional, computationally tractable computer simulation must be in place. I discuss this methodology—what I call recasting—and argue for its philosophical novelty. If these efforts are heading towards the right interpretation of simulation models, then one can show that computer simulations shed new light on the philosophy of science. To illustrate the potential of my interpretation of simulation models, I briefly discuss simulation-based explanations as a novel approach to questions about scientific explanation. (shrink)

Several prominent philosophers of science, most notably Ron Giere, propose that scientific theories are collections of models and that models represent the objects of scientific study. Some, including Giere, argue that models represent in the same way that pictures represent. Aestheticians have brought the picturing relation under intense scrutiny and presented important arguments against the tenability of particular accounts of picturing. Many of these arguments from aesthetics can be used against accounts of representation in philosophy of science. I rely on (...) Dominic Lopes' recent summary of arguments against various views of picturing and reformulate some of them to fit the philosophy of science context. My specific targets here are Giere and Steven French. I go on to argue that assuming all scientific models and images represent in the same way is not the best guide to understanding scientific practice. (shrink)

In this paper, I defend the view that there are many scientific images that have a serious epistemic role in science but this role is not adequately accounted for by the going view of representation and its attendant theoretical commitments. The relevant view of representation is Laura Perini’s account of representation for scientific images. I draw on Adina Roskies’ work on scientific images as well as work on models in science to support my conclusion.

Although scientific images have begun to receive significant attention from philosophers, one type of image has thus far been ignored: moving images. As techniques such as live cell imaging and videomicroscopy are becoming increasingly important in many areas of biology, however, this oversight needs to be corrected. Biologists often claim that there are relevant differences between video and static images. Most interesting is the idea that video images allow us to see causal relationships. By identifying the conditions that would be (...) required for this to be true and showing that they are not satisfied at the micro level, I will show that videomicroscopy does not provide us with special access to causal information. †To contact the author, please write to: Department of Philosophy, University of Calgary, 2500 University Dr. NW, Calgary, Alberta T2N 1N4; e-mail: [email protected]. (shrink)

Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the hierarchical (...) nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way. (shrink)

ArgumentThe use of diagrams is pervasive in theoretical physics. Together with mathematical formulae and natural language, diagrams play a major role in theoretical modeling. They enrich the expressive power of physicists and help them to explore new theoretical ideas. Diagrams are not only heuristic or pedagogical tools, but they are also tools that enable developing the content of models into novel implications.

Abstract In this essay, I will argue that images can play a substantial role in argumentation: exploiting information from the context, they can contribute directly and substantially to the communication of the propositions that play the roles of premises and conclusion. Furthermore, they can achieve this directly, i.e. without the need of verbalization. I will ground this claim by presenting and analyzing some arguments where images are essential to the argumentation process. Content Type Journal Article Pages 1-14 DOI 10.1007/s10503-011-9259-y Authors (...) Axel Arturo Barceló Aspeitia, Instituto de Investigaciones Filosóficas, Universidad Nacional Autónoma de México, Cto. Mario de la Cueva s/n, Cd. Universitaria, Coyoacán, 04500 DF, Mexico Journal Argumentation Online ISSN 1572-8374 Print ISSN 0920-427X. (shrink)

Recent philosophical analyses of the epistemic dimension of images in the sciences show a certain trend in acknowledging potential roles of these images beyond their merely decorative or pedagogical functions. We argue, however, that this new debate has yet paid little attention to a special type of pictures, we call ‘visual metaphor’, and its versatile heuristic potential in organizing data, supporting communication, and guiding research, modeling, and theory formation. Based on a case study of Conrad Hal Waddington’s epigenetic landscape images (...) in biology, we develop a descriptive framework applicable to heuristic roles of various visual metaphors in the sciences. (shrink)

Recent philosophical analyses of the epistemic dimension of images in the sciences show a certain trend in acknowledging potential roles of these images beyond their merely decorative or pedagogical functions. We argue, however, that this new debate has yet paid little attention to a special type of pictures, we call ‘visual metaphor’, and its versatile heuristic potential in organizing data, supporting communication, and guiding research, modeling, and theory formation. Based on a case study of Conrad Hal Waddington’s epigenetic landscape images (...) in biology, we develop a descriptive framework applicable to heuristic roles of various visual metaphors in the sciences. (shrink)

In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning distinct senses. The ‘new mechanisms’ (...) sense is at the center of most of these contemporary debates and will be treated at greater length; subsequent senses of mechanism will be primarily distinguished from this one. In part I of this paper, I distinguish two senses of the term ‘mechanism’, both of which are explicitly hierarchical and nested in character, such that any given mechanism is comprised of smaller sub-mechanisms, in turn comprised of yet smaller sub-sub-mechanisms and so on. While both of the senses discussed here are anti-reductive, they differ in their focus on scientific practice versus metaphysics, in the degree of regularity they attribute to mechanisms, and in terms of their relationships to the discussions of mechanisms in the history of philosophy and science. (shrink)

Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...) ideas that scientific models are ‘similar’, or structurally morphic, to their target systems. I argue that these approaches are misguided, and that at best these relationships concern the accuracy of a pre-existing representational relationship. I also pay particular attention to the sense in which target systems can be appropriately taken to exhibit a ‘structure’, and van Fraassen’s recent argument concerning the pragmatic equivalence between representing phenomena and data. My next target is the idea that models should not be seen as objects in their own right, but rather what look like descriptions of them are actually direct descriptions of target systems, albeit not ones that should be understood literally. I argue that these approaches fail to do justice to the practice of scientific modelling. Finally I turn to the idea that how models represent is grounded, in some sense, in their inferential capacity. I compare this approach to anti-representationalism in the philosophy of language and argue that analogous issues arise in the context of scientific representation. Part iii contains my positive proposal. I provide an account of scientific representation based on Goodman and Elgin’s notion of representation-as. The result is a highly conventional account which is the appropriate level of generality to capture all of its instances, whilst remaining informative about the notion. I illustrate it with reference to the Phillips-Newlyn machine, models of proteins, and the Lotka-Volterra model of predator-prey systems. These examples demonstrate how the account must be understood, and how it sheds light on our understanding of how models are used. I finally demonstrate how the account meets the desiderata laid out at the beginning of the thesis, and outline its implications for further questions from the philosophy of science; not limited to issues surrounding the applicability of mathematics, idealisation, and what it takes for a model to be ‘true’. (shrink)