A Guide to English: Data Visualization

"From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models--from linear regression to random walks and far beyond--that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage." - from the publisher

"As machine-readable data comes to play an increasingly important role in everyday life, researchers find themselves with rich resources for studying society. The novel methods and tools needed to work with such data require not only new knowledge and skills, but also a new way of thinking about best research practices. This book critically reflects on the role and usefulness of big data, challenging overly optimistic expectations about what such information can reveal, introducing practices and methods for its analysis and visualisation, and raising important political and ethical questions regarding its collection, handling, and presentation." - from the publisher

"A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data.How can we see a billion images? What analytical methods can we bring to bear on the astonishing scale of digital culture--the terabytes of photographs shared on social media every day, the hundreds of millions of songs created by twenty million musicians on Sound Cloud, the content of four billion Pinterest boards? In Cultural Analytics, Lev Manovich presents concepts and methods for computational analysis of cultural data, with a particular focus on visual media. Drawing on more than a decade of research and projects from his own lab, Manovich--the founder of the field of cultural analytics--offers a gentle, nontechnical introduction to selected key concepts of data science and discusses the ways that our society uses data and algorithms.Manovich offers examples of computational cultural analysis and discusses the shift from new media to more media; explains how to turn cultural processes into computational data; and introduces concepts for exploring cultural datasets using data visualization as well as other recently developed methods for analyzing image and video datasets. He considers both the possibilities and the limitations of computational methods, and how using them challenges our existing ideas about culture and how to study it. Cultural Analytics is a book of media theory. Arguing that before we can theorize digital culture, we need to see it, and that, because of its scale, to see it we need computers, Manovich provides scholars with practical tools for studying contemporary media."

"In the age of big data and digital distribution, when news travel ever further and faster and media outlets compete for a fleeting slice of online attention, information graphics have swept center stage. At once nuanced and neat, they distill abstract ideas, complex statistics, and cutting-edge discoveries into succinct, compelling, and masterful designs. Cartographers, programmers, statisticians, designers, scientists, and journalists have developed a new field of expertise in visualizing knowledge. This XL-sized compendium explores the history of data graphics from the Middle Ages right through to the digital era. Curated by Sandra Rendgen, some 400 milestones span astronomy, cartography, zoology, technology, and beyond. Across medieval manuscripts and parchment rolls, elaborate maps, splendid popular atlases, and early computer-based information design, we systematically break down each work's historical context, including such highlights as Martin Waldseemüller's famous world map, the meticulous nature studies of Ernst Haeckel, and many unknown treasures." - from the publisher

"An analysis of visual epistemology in the digital humanities, with attention to the need for interpretive digital tools within humanities contexts. In the several decades since humanists have taken up computational tools, they have borrowed many techniques from other fields, including visualization methods to create charts, graphs, diagrams, maps, and other graphic displays of information. But are these visualizations actually adequate for the interpretive approach that distinguishes much of the work in the humanities? Information visualization, as practiced today, lacks the interpretive frameworks required for humanities-oriented methodologies. In this book, Johanna Drucker continues her interrogation of visual epistemology in the digital humanities, reorienting the creation of digital tools within humanities contexts. Drucker examines various theoretical understandings of visual images and their relation to knowledge and how the specifics of the graphical are to be engaged directly as a primary means of knowledge production for digital humanities. She draws on ideas from aesthetics, critical theory, and formal study of graphical systems, addressing them within the specific framework of computational and digital activity as they apply to digital humanities. Finally, she presents a series of standard problems in visualization for the humanities (including time/temporality, space/spatial relations, and data analysis), posing the investigation in terms of innovative graphical systems informed by probabilistic critical hermeneutics. She concludes with a brief sketch of discovery tools as an additional interface into which modeling can be worked." - from the publisher