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This is an overview of the visualization and interaction experiments I produced for my Masters Thesis “Visual tools for the socio–semantic web” (.pdf, 12MB).
Project: BC Budget Visualization Tool
Date: September, 2009
Language: Processing
Key Concepts: Data visualization, data organization, sticking it to the man
Project: NYTimes 365/360
Date: February, 2009
Language: Processing
Key Concepts: Data Visualization, NYTimes Article Search API, HashMaps & ArrayLists
Good Data Viz can illuminate and educate, inspire and entertain. I also understand that this is an area when I am a student and am happy to turn it over to the pros. So, with this post I want to share some of the smartest stuff I’ve seen, as well as provide you with some original commentary from Patricia McDonald, Planning Director at BBH Labs.
Over the past few months I’ve been talking with many people passionate about Information Visualization who share a sense of saturation over a growing number of frivolous projects. The criticism is slightly different from person to person, but it usually goes along these lines: “It’s just visualization for the sake of visualization”, “It’s just eye-candy”, “They all look the same”.
I like to compare this practice to a game designer who lays out an intended context, rules and narrative for the game, but then has this moment of delight when users engender their own narrative, their own path. This is intrinsic to the conception of Information Visualization as a discovery tool.
Orthogonal to these strategies, which revolve around the nature and scale of content being created, there are those sites with look to aggregation methods across a variety of data types (from weblog feeds to traffic news streams). In addition, there are various services and technologies which can enhance the data and provide some plugin style publishing components (e.g. maps with events pinned on them) for hyperlocal sites to leverage.
As data visualization often needs to reach a broad audience the browser is becoming the number one tool to publish and share visualizations. A lot of visualizations require user-interaction to unleash their full potential, thus interactive applets that run directly in the browser are a a great way to analyze the data at hand. Beside the usual suspects like Flash, Silverlight and Processing, JavaScript is quickly gaining ground in the field of interactive visualization embedded in websites. We’ve collected 13 16 JavaScript visualization libraries that help you get started faster, keep it flexible and develop with higher reliability.
Every time that you login into your local Unix-like machine or a remote hosting server through a FTP client to upload a file or use SSH to get your stuff done, you’re leaving behind a trail of evidence showing your online behaviour: where and when you log in, how often and how long your online sessions are, in short: your modus operandi. This visualization tool unveils this hidden data, which is gathered by running a few builtin UNIX commands and is analyzed onsite.
A Sunburst visualization is a radial space-filling visualization technique for displaying tree like structures. There are other space-filling visualization methods that use other visual encodings for describing hierarchies. For example, the Treemap is a space-filling visualization that uses “containment” to show “parent-child” relationships.
Gource is a software version control visualization tool for Git and CVS.
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Wrapping your brain around data online can be challenging, especially when dealing with huge volumes of information. And trying to find related content can also be difficult, depending on what data you’re looking for. But data visualizations can make all of that much easier, allowing you to see the concepts that you’re learning about in a more interesting, and often more useful manner. Below are 50 of the best data visualizations and tools for creating your own visualizations out there, covering everything from Digg activity to network connectivity to what’s currently happening on Twitter.
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With all of the available tools to help you visualize data, it can be confusing where to start. The good news is, well, that there are a lot of (free) available tools out there to help you get started. It's just a matter of deciding which one suits you best. This is a guide to help you figure that out.
13 JavaScript visualization libraries that help you get started faster, keep it flexible and develop with higher reliability.
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Processing for the Web is a proposed Mozilla-sponsored initiative to create a complete and robust port of the Java-based Processing language and environment (popular for art, design, and visualization applications) to the open web, using standard technologies such as JavaScript, Canvas, etc.
One of the 8 works I created for the Data Art Show at the Pink Hobo Gallery in Minneapolis.
All these pieces are a pun on the new craze for data visualization. The goals of data visualization as I understand them are to make complicated issues more understandable, to make obscured connections visible and to reveal hidden patterns in the data. After all these tasks have been solved ideally the result should be aesthetically pleasing as well.
But when I look around what is being done in data visualization today I have the suspicion that in many cases the design is more important than the actual information and that the use of data is more an excuse to justify the use of aesthetics.
Since I do not have a problem with aesthetics for their own sake in these pieces I deliberately took the opposite direction. Since I wanted to create something visually interesting I made up my own data which would give me the desired results. All these works are the result of generative algorithms, so all the elements and their connections are actually data and not something I assembled manually in Illustrator.
Axiis is an open source data visualization framework designed for beginner and expert developers alike.
Data visualization is the use of tools to represent data in the form of charts, maps, tag clouds, animations, or any graphical means that make content easier to understand. Graphic representations of data are popular because they open up the way we think about data, reveal hidden patterns, and highlight connections among elements. Because current web applications allow anyone with access to data to enter information and easily create a virtualization of it, students, informal learners, and the purely curious can now easily create visualizations that might reveal trends that were not obvious from the numbers alone.
After The New York Times and The Guardian recently opened their online archives to the public, artists rushed to dissect nearly two centuries worth of information, elevating this art form to new prominence.
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