Visactivism

"Global Economic Dynamics project exists to help make complex economic dynamics transparent and understandable. The project examines the causes and effects of economic trends, as well as the connections linking one trend to another."

Stephen Few

What if the new way to get us to care is with a visceral, raw display of data?"

The result must be readable and recognizable. The most important criteria is that the visualization must provide a way to learn something about the data. Any transformation of non-trivial data into an image will leave out information, but there must be at least some relevant aspects of the data that can be read. The visualization must also be recognizable as one and not pretend to be something else."

"The visual representation of data has gone through a number of phases, with its goals switching back and forth between analysis and presentation over time. Many introductions to visualization tend to portray historical examples as all being done for the same purpose. That, I argue in this short, incomplete, and cherry-picked history, is not true."

"Ultimately, I believe the solution is a two-way street. First, anyone building a data visualisation must go to great lengths not only to link to sources and to fully explain any caveats relating to the data or graphic itself, but to state the degree to which their work should - or more importantly shouldn't - be taken as scientific fact. And second, we must better inform the wider public of the danger signs to watch out for before spreading what may turn out to be misinformation."

But the very feature that makes algorithms so valuable - their ability to replicate human decision-making in a fraction of the time - can be a double-edged sword. If the observed human behaviours that dictate how an algorithm transforms input into output are flawed, we risk setting in motion a vicious circle when we hand over responsibility to The Machine."

Unlike any time before in our lives, we have access to vast amounts of free information. With the right tools, we can start to make sense of all this data to see patterns and trends that would otherwise be invisible to us. By transforming numbers into graphical shapes, we allow readers to understand the stories those numbers hide. In this practical introduction to understanding and using information graphics, you’ll learn how to use data visualizations as tools to see beyond lists of numbers and variables and achieve new insights into the complex world around us. Regardless of the kind of data you’re working with–business, science, politics, sports, or even your own personal finances–this book will show you how to use statistical charts, maps, and explanation diagrams to spot the stories in the data and learn new things from it. 

Este mundo de esquemas, diagramas, redes, organigramas, sociogramas, cronogramas, graficos de flujos, etcetera, no disminuira en absoluto sino que, al contrario, estos son el signo de su crecimiento, con el progreso tecnologico y la creatividad grafica como lenguaje universal. Este libro nos descubre una perspectiva inedita: la visualizacion de los "fenomenos invisibles." Es el dominio de los lenguajes graficos hoy reunidos y estudiados sistematicamente, por primera vez, por Joan Costa, a la luz de la nueva ciencia de la comunicacion visual, la esquematica, a la que el autor ha definido como el "tercer lenguaje," despues de la imagen y el signo.

A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data.

Kim Rees, Periscopic co-founder

Jack Porway

Same data, democrat versus republican views…

We live in the era of Big Data, with storage and transmission capacity measured not just in terabytes but in petabytes (where peta- denotes a quadrillion, or a thousand trillion). Data collection is constant and even insidious, with every click and every "like" stored somewhere for something. This book reminds us that data is anything but "raw," that we shouldn't think of data as a natural resource but as a cultural one that needs to be generated, protected, and interpreted. The book's essays describe eight episodes in the history of data from the predigital to the digital. Together they address such issues as the ways that different kinds of data and different domains of inquiry are mutually defining; how data are variously "cooked" in the processes of their collection and use; and conflicts over what can -- or can't -- be "reduced" to data. Contributors discuss the intellectual history of data as a concept; describe early financial modeling and some unusual sources for astronomical data; discover the prehistory of the database in newspaper clippings and index cards; and consider contemporary "dataveillance" of our online habits as well as the complexity of scientific data curation.

We have on stage: Kim Rees co-founder of Periscopic, a data visualization company guided by the motto: “do good with data” and Jake Porway, founder of Data Kind, an organization that brings together data scientists and social organizations. We discuss about the challenges of working in this crazy world of big data opportunities and counterbalance this with risks and subtle potentially negative implications.

The remarkable thing about the data revolution is not that it has changed our lives so much, but that it hasn’t changed it enough.