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Why d3 Will Change How We Publish Maps. Publishing maps to the web.

Why d3 Will Change How We Publish Maps

Simple right? Data Visualization for the Web. Create: Information Wheel. Today I am releasing a tool that allows users to create and export an Information Wheel.Click here to access the tool.

Create: Information Wheel

The top 20 data visualisation tools. One of the most common questions I get asked is how to get started with data visualisations. Beyond following blogs, you need to practise – and to practise, you need to understand the tools available. In this article, I want to introduce you to 20 different tools for creating visualisations: from simple charts to complex graphs, maps and infographics. Almost everything here is available for free, and some you have probably installed already. Advertisement Entry-level tools.

Perceptual Edge’s 2012 Dashboard Design Competition. A few weeks ago I mentioned in this blog that I would soon announce the 2012 Perceptual Edge Dashboard Design Competition.

Perceptual Edge’s 2012 Dashboard Design Competition

Today, the competition officially begins. This will be the most challenging event of this type to date resulting in the most esteemed award for dashboard design (in my not-so-humble opinion) since I judged a similar competition for the B-Eye-Network back in 2006. This competition will serve several purposes: A showcase for the current state of expert dashboard design.An opportunity for me to use the submissions to teach best practices by critiquing several of them on this website and in the second edition of the book Information Dashboard Design, which I am currently writing.An opportunity to provide sample dashboard designs that could actually be used to improve the quality of education in schools, for this competition involves the design of a dashboard that could be used by teachers to monitor the performance of their students.

Here are the basic facts: Take care, Unfolding - Interactive Map Library for Processing and Java. Unfolding Library for Interactive Maps. Expressing UX Concepts Visually. By Barnabas Nagy Published: May 7, 2012.

Expressing UX Concepts Visually

Online and Open-Source Resources for Data Sourcing, Visualization, and Analysis - Professor Bear Braumoeller. A tutorial on visualizing numeric data by groups A blog about how the New York Times does its visualizations All-in-One Examples: Data + Visualization Wolfram's massively useful general knowledge engine, Wolfram Alpha.

Online and Open-Source Resources for Data Sourcing, Visualization, and Analysis - Professor Bear Braumoeller

Five of the Guardian Datablog's best visualisations. Guardian Datastore editor Simon Rogers: Rogers said: 'We're not just data analysers, we've become data providers' Data is the "new normal" in journalism, according to Simon Rogers, the editor of the Guardian’s Datablog and Datastore.

Five of the Guardian Datablog's best visualisations

The aim of the Guardian when it comes to data is to guide the public through the mass of information available and present it in an attractive and easy-to-understand format. Speaking at the PPA (Professional Publishers Association) conference this week Rogers said: "What's happening is we're not just data analysers, we've become data providers. Try the VIDI Wizard: Build and Embed Visualizations. Why has Data Visualization Become so Popular? Not all that long ago, when someone mentioned data visualization images, graphics printed in the USA Today, New York Times or the Economist would instantly come to mind – not any more.

Why has Data Visualization Become so Popular?

Over the last two to three years there has been an explosion in the popularity of data visualization. There’s no question that data visualization is hot right now, but why? Why have we become so fascinated with data visualization? How to Pick a Chart for Your Dashboard. As Dashboard Spy readers know, dashboard chart selection is fraught with peril and the subject of many books and blogs.

How to Pick a Chart for Your Dashboard

I’ve written at length about the relative merits of different chart types and stress how the decision of which chart to use should not be made frivolously nor at random. To help you (or perhaps to confound you further), I present the “Chart Chooser” or aka “Chart Selections Thought Starter” from www.extremepresentation.com. Take a look at this screengrab of the graphic and I’ll give you a higher resolution pdf link below the chart. For a larger pdf, use this link: Infographic vs. Data Visualization (Who Cares?) The more visually inclined we become in our quest to consume information, the blurrier the line between data vis and infographic gets.

Infographic vs. Data Visualization (Who Cares?)

To the great dismay of art directors, designers, etc. these terms are even being used interchangeably. For clarification, I went digging around the Web and found a pretty great summation of the differences from Nick Iliinsky: “Infographics are the ones that are usually illustrated by a graphic designer; they’re probably done in Illustrator, there’s some data in them, but they’re not necessarily data-rich. They tend to be manually authored, manually constructed — obviously on a computer — but somebody sat down and said, “we’re going to put the big windmill here for ‘more windpower’ and more sunshine for ‘more solar power’ and a smaller oil barrel here” or whatever. That’s an infographic. In other words, the real difference between these guys is in the process. In the end, they’re both lookers. Communication Rules Image credit: informationisbeautiful.net.

R, Octave, and Python: A Follow-Up. In my recent article posted on May 16, I compared functionalities for R, Octave and Python at a very high level.

R, Octave, and Python: A Follow-Up

The article received many insightful comments. I wanted to share what the commenters had to say—this follow-up is to clarify or expand upon some of the points raised. Miso: An open source toolkit for data visualisation. R training: Visualization, Big Data, Data Mining, and Marketing Analytics. Revolution Analytics is hosting several live and online courses over the next couple of months that will be of interest to R users looking to hone their skills: Visualization in R with ggplot2. Garrett Grolemund and Winston Chang instruct how to use the ggplot2 package to make, format, label and adjust graphs using R.

(August 28, Redwood City, CA.)Big Data Analytics with RevoScaleR. Battle of the Charts: Why Cartesian Wins Against Radial. Undeniably, radial charts based on a polar coordinate system are more visually appealing than regular line, area and bar charts, or even tree maps, all of which are based on a cartesian coordinate system. Unfortunately, they are rarely better at communicating information. Radial charts are things like radar charts, Coxcomb charts, radial bar charts, or radial tree maps. These charts are all very visually interesting. The have relationships that our brain can easily detect, but that are hard for us to interpret. This duality is why they are more beautiful, but at the same time worse, for showing data.

Visualizing Massive Amounts of Big Data. At the end of the day, the whole point of a business intelligence (BI) application is to make it easier to discern patterns and trends that would otherwise not be obvious. As such, the competition between BI applications is ultimately going to come down to which one best fulfills that mission, especially in an era where Big Data is making massive amounts of information readily available. Pentaho upped its game in that regard with release today of version 4.5 of its namesake open source BI application, which enhances the application's core visualization engine with new geo-mapping, heat grids, scatter/bubble chart visualizations, interactive visual analysis capabilities such as lasso filtering, zoom and attribute highlighting on all chart types, and a variety of reporting enhancements. The good news is that rather than extrapolating insights based on a thin slice of data, NoSQL databases make it easier and more affordable to base decisions on large sets of complete data.

Interactive Dynamics for Visual Analysis. Jeffrey Heer, Stanford University Ben Shneiderman, University of Maryland, College Park The increasing scale and availability of digital data provides an extraordinary resource for informing public policy, scientific discovery, business strategy, and even our personal lives. To get the most out of such data, however, users must be able to make sense of it: to pursue questions, uncover patterns of interest, and identify (and potentially correct) errors.

In concert with data-management systems and statistical algorithms, analysis requires contextualized human judgments regarding the domain-specific significance of the clusters, trends, and outliers discovered in data. The Miso Project. The Audacity of the Visually Inclined. Michael Dillon Scott has a very bold face. Twitter analysis of air pollution in Beijing. One of the air pollution detection machine in Beijing (at the American Embassy) is connected to Twitter and tweet about the air quality in real time. By default the machine in Beijing output the 24hr summary PM2.5 air pollution information. Creating Stunning Visualizations With Impress.js. Emergent Futures Mapping with Futurescaper. Futurescaper is an online tool for making sense of the drivers, trends and forces that will shape the future. Visualizing 2012 census estimates using CartoDB and Leaflet. I’ve been tinkering around with some new mapping tools lately, and figured I’d put them to good use by displaying the 2011-2012 population estimates released last week by the U.S.

Learning data visualization. Travis Kochel’s FF Chartwell. Newly launched – The Miso Project. This week has seen the launch of The Miso Project, an “open source toolkit designed to expedite the creation of high-quality interactive storytelling and data visualisation content”. Why does Data Visualization Matter? Over the last couple months, I’ve written several posts trying to help those designers create better visuals. How data visualization turns scientists into storytellers. Wordle - Beautiful Word Clouds. How to Make an Interactive Network Visualization. Fancy HTML5 Slides with knitr and pandoc.

More on Horizon Charts. Hadley Wickham’s ggplot2 basics. C2: Clojure/ClojureScript data visualization - Clojure. Four Easy Visualization Mistakes to Avoid. List of Hand-Picked and Recommended Data Visualization Tools. Bio7 1.6 for Windows and Linux released! Gephi Toolkit Tutorial. Gaphi. Mobile User Interface (UI) Kits for Designers. Notch launches to creatively visualize data captured by consumer fitness devices. Quadrigram: New visual programming environment launches. It’s Time to Practice Decision Visualization. Data Visualization Techniques for Those Who Can’t Draw. Visualisation Devices from Filip on the Behance Network. Geospatial Visualization. FF Chartwell: Make cool graphs by simply typing. Data Visualization: Clarity or Aesthetics? 38 visualization api.

Useful scripts to plot charts in web pages. What we can learn about charts from The WSJ Guide to Information Graphics. World’s tallest tower – Burj Dubai. The Charts That Should Accompany All Discussions of Media Bias - James Fallows. The Design Choices You Make for Information: How to Create Great Data Visualizations. Storytelling: The Next Step for Visualization. Papers/2013/Kosara_Computer_2013.pdf. Seven dirty secrets of data visualisation. 28 Rich Data Visualization Tools. Making infographics using R and Inkscape.