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How can cartoon images aid in understanding bacterial biological processes? What prompts physicists to blur their images before showing them to biologists? Considering that the astronomer’s data consists solely of invisible, electric impulses, what is the difference between representing outer space as images, graphs, or sound? How does a work of contemporary art differ from a scientific image if we cannot visually distinguish between the two? How do aesthetics, art, and design influence scientific visualization and vice versa? This volume asks critically important questions about scientific data representation and provides significant insights to a field that is interdisciplinary in its very core. The authors investigate scientific data representation through the joint optics of the humanities and natural sciences. The volume particularly appeals to scholars in visual and aesthetic studies, data visualization, scientific illustration, experience culture, information design, and science communication.
What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization? Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole. Drawing from their unconventional backgrounds, these two women take readers through a journey around perception, semantics, and intent as the triad that influences visualization. This visually engaging book blends ideas from theory, academia, and practice to craft beautiful, yet meaningful visualizations and dashboards. How do you take your visualization skills to the next level? The book is perfect for analysts, research and data scientists, journalists, and business professionals. Functional Aesthetics for Data Visualization is also an indispensable resource for just about anyone curious about seeing and understanding data. Think of it as a coffee book for the data geek in you. https://www.functionalaestheticsbook.com
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story
This book investigates a new interactive data visualisation concept that employs traditional Chinese aesthetics as a basis for exploring contemporary digital technological contexts. It outlines the aesthetic approach, which draws on non-Western aesthetic concepts, specifically the Yijing and Taoist cosmological principles, and discusses the development of data-based digital practices within a theoretical framework that combines traditional Taoist ideas with the digital humanities. The book also offers a critique of the Western aesthetics underpinning data visualisation, in particular the Kantian sublime, which prioritises the experience of power over the natural world viewed at a distance. Taoist philosophy, in contrast, highlights the integration of the surface of the body and the surface of nature as a Taoist body, rather than promoting an opposition of mind and body. The book then explores the transformational potential between the human body and technology, particularly in creating an aesthetic approach spanning traditional Chinese aesthetics and gesture-based technology. Representing a valuable contribution to the digital humanities, the book helps readers understand data-based artistic practices, while also bringing the ideas of traditional Chinese aesthetics to Western audiences. In addition, it will be of interest to practitioners in the fields of digital art and data visualisation seeking new models.
This book constitutes the refereed proceedings of the 14th International Conference on Interactive Digital Storytelling, ICIDS 2021, held in Tallinn, Estonia, in December 2021. The 18 full papers and 17 short papers, presented together with 17 posters and demos, were carefully reviewed and selected from 99 submissions. The papers are categorized into the following topical sub-headings: Narrative Systems; Interactive Narrative Theory; Interactive Narrative Impact and Application; and the Interactive Narrative Research Discipline and Contemporary Practice.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Information may be beautiful, but our decisions about the data we choose to represent and how we represent it are never neutral. This insightful history traces how data visualization accompanied modern technologies of war, colonialism and the management of social issues of poverty, health and crime. Discussion is based around examples of visualization, from the ancient Andean information technology of the quipu to contemporary projects that show the fate of our rubbish and take a participatory approach to visualizing cities. This analysis places visualization in its theoretical and cultural contexts, and provides a critical framework for understanding the history of information design with new directions for contemporary practice.
Graphical practice. Theory of data graphics.
The dissertation, Animate Biology: Data, Visualization, and Life's Moving Image, develops a concept of scientific aesthetics in order to counter the neoliberalization of scientific visualization practices. In particular, the dissertation investigates how 3D molecular animation is a visualization practice that uses technologies developed by the entertainment industry (Pixar and DreamWorks) to animate data sets. The project shows how there is controversy among scientists regarding the scientific value of using this technology, since scientists disagree over whether computer animation is capable of accurately visualizing biological data. Drawing on Lorraine Daston and Peter Galison's scholarship on the history of scientific visualization, the dissertation intervenes in this debate by arguing (1) that representation, instead of objectivity, is the epistemic norm that determines the scientific value of images, and (2) that representation is fully operative in 3D molecular animations. I argue that what is often missed in debates over the value of computer animation is that representation has undergone many transformations in the history of scientific epistemology, and that it now obeys the logic of flexibility and competition that exemplifies neoliberal market values. In other words, the problem with molecular animation is that representation determines its scientific value, and this is what needs to be overcome. Over the course of four chapters, the dissertation uses the methods of media archeology to discover a genealogy for scientific visualization that does not rely on the values of representation; it will then use this as the basis for generating non-representational values for computer animation in biology. The dissertation contends that an aesthetics of the scientific image developed out of the twentieth-century avant-garde science films of Jean Painlev', as well as the aesthetic philosophies of Immanuel Kant and Gilles Deleuze, offers a genealogical and conceptual framework to understand how computer animation could become a visual medium for scientific aesthetics that resists neoliberal value production in science. The first chapter, "Molecular Control," situates molecular animation within the field of biological data visualization, and argues that the distinct advantage of the technology, according to its proponents, is that it gives spatial and temporal form to invisible and static data sets. However, opponents argue that the technology takes far too many liberties with the interpretation of data, and so does not provide a reliable form of visualization. Relying on scholarship from Daston, Galison, and other historians of science, the project investigates the historical emergence of epistemic norms in scientific imaging, and demonstrates that what has remained constant, at least since the eighteenth century, is the value of representation (and not objectivity). The chapter takes issue, however, with Daston and Galison's insistence that the limitless recombination and flexibility of digital and nano imaging spells the end of representation in scientific visualization. Drawing on work by Michel Foucault, Gilles Deleuze, Alexander Galloway, among others, the chapter argues that representation is still the dominant epistemic value in scientific imaging, it's just that it has undergone a fundamental transformation: it now obeys the rationality of the neoliberal market. Using this framework, the chapter demonstrates how computer animation, especially with its development of automated design techniques, exemplifies representational values in neoliberalized technoscience. In this way, molecular animation testifies to the latest shift in scientific representation, and also exposes the limitation of more "internalist" histories of science, such as Daston and Galison's, inasmuch as they are too often blind to the co-production of market and epistemic values. The second chapter, "Micro and Nano Imaging," investigates two case studies from the history of scientific imaging that appear to thwart representational values. In particular, the chapter inquires into whether these instances could provide a framework for non-representational values in scientific visuality. The first case study comes from early twentieth century molecular cinematography. Drawing on scholarship from Hannah Landecker and Lisa Cartwright, the project examines how the techniques of "micro-cinematography," introduced by Jean Comandon, Alexis Carrel, and others, made significant contributions to our understanding of the temporal development of living systems. However, micro-cinematography did not garner support from the wider scientific community. In fact, its extensive use of time-lapse techniques were often criticized by scientists for introducing too much "subjective" or "aesthetic" intervention into the observation of natural systems. But where the annals of science tend to write off micro-cinematography due to its failure to accurately represent natural systems, the dissertation shows how representation is very much at stake in these early moving images. Drawing on Daston and Galison's work once again, the chapter contends that micro-cinema relied on a form of representation that wouldn't take hold in scientific epistemology until decades later: namely, the uses of the scientist's "trained judgment." In other words, micro-cinema doesn't thwart or disregard representation; rather, it anticipates its transformation. The second case study that the chapter draws on is nanomanipulation. In this domain of technoscience, seeing the world through a microscope and bringing it into existence have merged into the same process. The chapter investigates current nanoimaging technologies that are indebted to the work of Don Eigler and Erhard Schweizer, who first used a scanning tunneling microscope (STM) in 1989 to write their company name, IBM, at the atomic scale. While humanities scholars, such as Luciana Parisi and Nathan Brown, have noted the aesthetic implications of nanotechnology, the dissertation contends that the meaning of the "aesthetic" has been subsumed under the values of engineer-scientists: each manipulation indexes future applications and markets rather than purely aesthetic, or creative, manipulations of matter. The project therefore demonstrates how nanoimaging is still beholden to representational values, even though the technology alters matter as it views it. Overall, the chapter contends that neither micro nor nano imaging thwart representation as the premiere value in scientific imaging, and that each practice upholds representation, but only insofar as it finds a way to incorporate aesthetics into its logic. The third and fourth chapters of the dissertation then investigate how the "aesthetic" could become a form of resistance to scientific representation, by inquiring into whether there are instances of visual aesthetics in science that cannot be incorporated into representational values. To this end, Chapter three, "The Scientific Avant-Garde," considers work from a scientific filmmaker who has always been on the fringes of scientific acceptability: Jean Painlevé. In particular, the chapter examines Painlev's fraught relation to the scientific community, and his subsequent embrace of avant-garde filmmakers and painters, especially the Surrealists. Through a close analysis of several decades of Painlevé's work, especially from the 1920s to the 1960s, the chapter shows how he sought to undermine the persistence of anthropocentrism in science film by using formal techniques that he shared with other avant-garde filmmakers.
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