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Gallery: How networks help us understand the world As designer Manuel Lima points out in his TED Talk, A visual history of human knowledge, the network has become a powerful way to visualize much of what is going on in the world around us. “Networks really embody notions of decentralization, of interconnectedness, of interdependence,” says Lima. “This way of thinking is critical for us to solve many of the complex problems we are facing nowadays, from decoding the human brain to understanding the vast universe out there.” Here, Lima shares a few of his favorite network graphics. The Strengths of Nations This image shows the connections between scientific disciplines such as astrophysics, math and biochemistry. Visualizing the Bible This 2007 map by Chris Harrison shows 63,779 cross-references found in the Bible. flowerGarden This visualization by Greg Judelman and Maria Lantin shows the online discussion at a live event. Map of Science yFiles Although this looks like a piece of abstract art, there’s actually a lot going on here.

Your Random Numbers – Getting Started with Processing and Data Visualization Over the last year or so, I’ve spent almost as much time thinking about how to teach data visualization as I’ve spent working with data. I’ve been a teacher for 10 years – for better or for worse this means that as I learn new techniques and concepts, I’m usually thinking about pedagogy at the same time. Lately, I’ve also become convinced that this massive ‘open data’ movement that we are currently in the midst of is sorely lacking in educational components. This post, then, is a first sketch of what a lesson plan for teaching Processing and data visualization might look like. Let’s Start With the Data We’re not going to work with an old, dusty data set here. Even on a Saturday, a lot of helpful folks pitched in, and I ended up with about 225 numbers. I wrote a quick Processing sketch to scrape out the numbers from the post, and then to put them into a Google Spreadsheet. It’s about time to get down to some coding. Got it? Now we need to get our data from the spreadsheet. OK.

Latest As I mentioned in my previous post, our collaboration with the Sabeti Lab is aimed at creating new visual exploration tools to help researchers, doctors, and clinicians discover patterns and associations in large health and epidemiological datasets. These tools will be the first step in a hypothesis-generation process, combining intuition from expert users with visualization techniques and automated algorithms, allowing users to quickly test hypothesis that are “suggested” by the data itself. Researchers and doctors have a deep familiarity with their data and often can tell immediately when a new pattern is potentially interesting or simply the result of noise. In the last post, I went into some detail about the difficulties that arise when representing pairwise associations in a dataset that contains a mixture of numerical and categorical variables. There are many online materials on information theory and Shannon entropy, starting with the obligatory Wikipedia article.

The Work of Edward Tufte and Graphics Press Edward Tufte is a statistician and artist, and Professor Emeritus of Political Science, Statistics, and Computer Science at Yale University. He wrote, designed, and self-published 4 classic books on data visualization. The New York Times described ET as the "Leonardo da Vinci of data," and Business Week as the "Galileo of graphics." He is now writing a book/film The Thinking Eye and constructing a 234-acre tree farm and sculpture park in northwest Connecticut, which will show his artworks and remain open space in perpetuity. He founded Graphics Press, ET Modern gallery/studio, and Hogpen Hill Farms LLC. Visual Display of Quantitative Information 200 pages Envisioning Information 128 pages Visual Explanations 160 pages Beautiful Evidence 214 pages Same paper and printing as in original clothbound editions. All 4 clothbound books, autographed by author $150 Available directly from Graphics Press. Die visuelle Darstellung quantitativer Informationen, (200 Seiten), $12 数量情報の視覚的表示, (200 ページ)、$12

Ferran Adria – speaking at Google and his new book — In late September I was lucky enough to be able to hear Ferran Adria speak at Google, and also get a copy of his new cookbook. Ferran is one of the most famous chefs in the world; though lesser known in the US/UK since he doesn’t speak English and doesn’t have TV shows. His restaurant (elBulli) was named the best restaurant in the world for four years straight. What Ferran is really known for is his creativity. His talk was all about creativity, and was recorded below. I sat next to a woman who practices “visual notetaking” and grabbed her notes from the talk from Flickr. The points from her notes are clear. Another key perspective is that creativity depends on production. Finally, we all got/bought copies of his newest book, “The Family Meal.” There are a few awesome things about this book: The recipes are laid out as 31 complete 3-course meals (starter, main, dessert).

The Best Tools for Visualization Visualization is a technique to graphically represent sets of data. When data is large or abstract, visualization can help make the data easier to read or understand. There are visualization tools for search, music, networks, online communities, and almost anything else you can think of. Visualize Social Networks Last.Forward: Thanks to's new widget gallery, you can now explore a wide selection of extras to extend your experience. Last Forward Friends Sociomap: Friends Sociomap is another tools that generates a map of the music compatibility between you and your friends. Fidg't:Fidg't is a desktop application that gives you a way to view your networks tagging habits. Fidg't The Digg Tools: has some of the best web-based visualization tools on the net, so they're a must for any visualization list. One more: Digg Radar . YouTube: You can discover related videos using YouTube's visualizations. Visualize Music Musicovery music visual tools: Amazon Flickr

Une horloge avec Processing-Mozilla Firefox Quelques exemples de principes intéressants. Clock for Erg. La proposition dans le cadre du cours d’arts numériques : réaliser avec Processing une horloge qui tournera dans le hall de l’erg. Le script sera changé régulièrement pour permettre à toutes d’être utilisées. Lien : Processing : horloge. Un exemple basique sur le site de Processing. Michel Cleempoel : Horloges. Une foultitude d’exemples sur le site de Michel. Floss manuals : La ligne de temps. Des exemples d’horloges avec Processing. Mogen Jacobsen : Processing clock. Un essai original de Mogen Jacobsen. Lab[au] : Who’s afraid of Red, Green and Blue (2007). Le point de départ de cette série est la Tour Dexia a Bruxelles dont les 4200 fenêtres peuvent être éclairée individuellement par des rails de LED en RVB. Lab[au] : Chrono.prints - édition 2 + 1 (2009). Maarten Baas : Real Time - Grandfather Clock. Maarten Baas : Real Time - Sweepers clock. Albin Karlsson: 1g/min. Autres liens.

Matthew Ericson – The winners of the 34th Edition of the Best of News Design contest were released today, so I’ve updated my interactive crosstab of SND winners that lets you see at a glance which publications won awards in which categories. One particularly interesting thing to me: There were only 19 awards give in the information graphics categories — 17 for individual works and 2 for portfolios. That’s down from 97 just three years ago. I’d be curious to know how much of the decline comes from fewer print graphics being produced in general in newspapers — and probably also fewer entries in the contest — and how much is from a different, and much tougher, set of judges than in past years. Just pushed out an update to the Adobe Illustrator MultiExporter script that lets you specify if you want to export PNGs and JPGs at a different scale factor so that you can generate versions of the images at double resolution for iPhone retina displays. I’ve posted the slides from my presentation as a PDF.

Just Plain Data Analysis This is the companion website for the book: Gary Klass, Just Plain Data Analysis: Finding, Presenting, and Interpreting Social Science Data (New York: Rowman and Littlefield Publishers, 2008) ISBN: 978-0-7425-6053-6 Gary Klass, Just Plain Data Analysis: Finding, Presenting, and Interpreting Social Science Data(New York: Rowman and Littlefield Publishers, 2012) Second Edition ISBN: 978-1-4422-1508-5 What is Just Plain Data Analysis? [excerpt from the Preface] JUST PLAIN data analysis” is, simply, the compilation and presentation of numerical evidence to support and illustrate arguments about politics and public affairs. When contending sides advance their causes by finding, presenting, and interpreting such evidence with clear thinking, the quality of public debate and the chances of devising effective solutions to society’s problems are greatly increased. Why We should Teach Just Plain Data Analysis

Generation Flux: danah boyd

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