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Statistical Graphics and more » Blog Archive » Statistical Graphics vs. InfoVis

Statistical Graphics and more » Blog Archive » Statistical Graphics vs. InfoVis
The current issue of the Statistical Computing and Graphics Newsletter features two invited articles, which both look at the “graphical display of quantitative data” – one from the perspective of statistical graphics, and one from the perspective of information visualization. Robert Kosara writes from an InfoVis view: Visualization: It’s More than Pictures! Information visualization is a field that has had trouble defining its boundaries, and that consequently is often misunderstood. It doesn’t help that InfoVis, as it is also known, produces pretty pictures that people like to look at and link to or send around. But InfoVis is more than pretty pictures, and it is more than statistical graphics. The key to understanding InfoVis is to ignore the images for a moment and focus on the part that is often lost: interaction. … read on in the Newsletter. Andrew Gelman and Antony Unwin write from an statistical graphics view: Visualization, Graphics, and Statistics Related:  Introduction to Data VisualizationDataVis Tutorials - Principles

Can someone please stop the infographic madness? A few years ago, we started doing info graphics by actually doing a lot of research on data and then working with a great group of guys to create art and visualization. One of them was good enough to be linked from Apple’s website. Old magazine hands called these infographics, charticles. Wired and the old Red Herring were particularly good at this stuff. (No surprise, because my former editor and goddess of the charticle, Joanna Pearlstein works(worked) for both those publications.) Mint, a financial management company did a great job of using infographics to draw attention to their blog and by extension to their service. It is my belief that in modern times, no success goes unpunished. What has really happened is that social media experts discovered that people like to share infographics and many folks like to embed them in their tumblers and blogs. Like this: Like Loading...

Data visualisation: in defence of bad graphics | News Are most online data visualisations, well, just not very good? It's an issue we grapple with a lot - and some of you may have noticed a recent backlash against many of the most common data visualisations online. Poor Wordle - it gets the brunt of it. It was designed as an academic exercise that has turned into a common way of showing word frequencies (and yes, we are guilty of using it) - an online sensation. There's nothing like ubiquitousness to turn people against you. In the last week alone, New York Times senior software architect Jacob Harris has called for an end to word clouds, describing them as the "mullets of the Internet". While on Poynter, the line is that "People are tired of bad infographics, so make good ones" Awesomely bad infographics from How to Interactive Design Photograph: How To Interactive Design Grace Dobush has written a great post explaining how to produce clear graphics, but can't resist a cry for reason. What's the big deal? A little extreme, no? More open data

What Exactly Is Visualization? I love a good visualization. I’ve always been fascinated by those images that manage to inform and entertain at the same time. From time to time I’ve tried to supply tips and insight to help those interested in creating better visualizations. One morning while researching data visualizations I thought to myself “what really makes up visualization”, is it definable? So I did what most of us do when we’re in search for information; I Googled it. After a few minutes of clicking various links I came across an awesome post from Column Five Media that tries to explain what makes up good visualization that I wanted to share with you. Before I attempt to define what visualization is, let’s frame this discussion up a little bit. His early work really introduced the general public to data visualization. According to Yau, you need to think of data visualization as “a medium. The best way to define visualization is as Yau described it, as a medium. Related

Paper: Privacy-Preserving Visualization The point of visualization is usually to reveal as much of the structure of a dataset as possible. But what if the data is sensitive or proprietary, and the person doing the analysis is not supposed to be able to know everything about it? In a paper to be presented next week at InfoVis, my Ph.D. student Aritra Dasgupta and I describe the issues involved in privacy-preserving visualization, and propose a variation of parallel coordinates that controls the amount of information shown to the user. Naive Approaches As with everything else, there is an obvious solution to this problem that doesn’t work. While this is obviously useless for visualization, this is the way the data can be passed on to third parties without knowledge about what they are going to do with it, while guaranteeing a minimum level of privacy. A Visualization Solution But what if we know a bit more? The result is much fuzzier than regular parallel coordinates, but that is of course the point.

Guest Post: The Future of Data Visualization Data is everywhere - and readily accessible The open data movement is finally beginning to have some real impact. Governments are beginning to open up and give people access to the data they have rights to. Some corporations are realizing they don’t need to keep closed doors on all of their data, especially if they are doing the right thing anyway. The number of places to find open data on the web is growing rapidly, and shows no signs of slowing. A D3 visualization of unemployment in the US from Nathan Yau, data via the BLS Technology determines how we develop and consume visualizations The devices we use to view data visualizations have changed drastically with the advent of tablets, smartphones and other portable computing devices. Other technologies in the visualization chain are constantly evolving, as well. These trends set the stage for some pretty impressive changes in data visualization -- yet some things will not change. The chart types that exist are not going to change much.

An Information Visualization Exercise | Dashboard Spy Want to play a game with The Dashboard Spy and Information Visualization expert Stephen Few? In his blog post, The Billion Pound-o-Gram Redesigned, he takes a stab at redesigning a pretty well known chart by David McCandless. Take a look at the original chart here: Here is how it appeared in Guardian.co.uk’s Information is Beautiful Friday: The Billion Pound-o-Gram 289 billion spent on this. 400 billion spent on that. So, now for the game. Here is what he had to say: All of these comparisons are incredibly simple to make using the bar graph below. So, which version do you like and why? Hubert Lee The Dashboard Spy More business intelligence dashboards related to An Information Visualization Exercise

Scientists Say Infographics Can Save Morons From Themselves. Really? | Co.Design It’s a sad fact of our cultural moment that anyone can marshall their own "facts" to support just about any argument or political position imaginable. (Thanks, Internet.) What’s worse, psychology studies have shown that rebutting factually impoverished arguments with actual facts has precisely the opposite effect one would hope: it actually makes people cling even tighter to their fictions. Is there anything that can cut through this Gordian knot of nonsense? Political scientists Brendan Nyhan and Jason Reifler designed some experiments to test the efficacy of graphical "correctives" to inaccurate beliefs. Why might this be? But there’s a big hole in this whole conceit. Here’s a simple example. But you don’t even have to get all mathy and technical to pull a fast one with shoddy infographics. Regardless of whether Nyhan and Reifler’s results are sound, their hypothesis underscores the fact that visual communication is a powerful tool that can be used for good or ill.

How to create a terrible visualization The last couple of visualizations I've done have been complete flops, at least in terms of traffic. A geeky post about my profiling habits got more visitors than a shiny 3D globe! It's never fun to confront it but as Bob Sutton says; 'failure sucks but instructs'. Tell lots of stories at once I love exploring complex data sets, but it takes a lot of effort and time. Focus on the technology I'm completely technology-driven. Advanced technology like that is essential for a strong visualization, but you need something more on top. Copy a previous success People pass a link to their friends if they think it's remarkable, something they've not seen before. Leave out the magic One of the things I love about creating visualizations is that it's more art than a science. In the past I've effectively been goofing off when I was working on a new graph, procrastinating on my real work, but these days my responsibility for Jetpac is always in the back of my mind. Like this: Like Loading...

Information graphics Information graphics or infographics are graphic visual representations of information, data or knowledge intended to present complex information quickly and clearly.[1][2] They can improve cognition by utilizing graphics to enhance the human visual system’s ability to see patterns and trends.[3][4] The process of creating infographics can be referred to as data visualization, information design, or information architecture.[2] Overview[edit] Infographics have been around for many years and recently the proliferation of a number of easy-to-use, free tools have made the creation of infographics available to a large segment of the population. Social media sites such as Facebook and Twitter have also allowed for individual infographics to be spread among many people around the world. In newspapers, infographics are commonly used to show the weather, as well as maps, site plans, and graphs for statistical data. "Graphical displays should: Graphics reveal data. History[edit] Early[edit]

10 significant visualisation developments: 2011 Back in July I published a collection of the 10 most significant visualisation developments from the first half of 2011. These were a very personal view of the most prominent, memorable, significant, progressive and appealing developments of the year so far. As we prepare to bid farewell to 2011 I am now looking back over the latter half of the year with a follow up collection of developments that I perceive to have had most significance during the period July to December. As I made clear in the previous post, there will be selections here that won’t or wouldn’t make other peoples’ top 10s but I wouldn’t expect them to. These are just things that struck a chord with me and fulfill my basic criteria that they further the progress of data visualisation in their own particular way. And so, in no particular order… 1. 2. 3. It would difficult to argue against Moritz Stefaner being recognised as the most prolific, prominent and celebrated visualisation designer of 2011. 4. 5. 6. 7. 8. 9. 10.

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