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A visualization of perlin noise. The angle of each blue line is dependent upon the value of perlin noise at each x,y position.
Comparison of the number of my emails for March, 2006 from three people - a colleague, sister, and daughter.
After three hours in bed, I woke up with a bad sore throat. So I was nearly speechless - the whole day.
The former state of my infamously-decorated 1991 Pontiac Grand Am. When i bought the big, orange "Visualize Grilled Cheese" sticker at the 1997 HORDE festival, I did so because I thought it was completely random, stupendous and hysterical. but since then, I've broadened my horizons a bit. Now, I believe it's a direct response to another, equally anonymous bumper sticker, which reads "Visualize Whirled Peas."
This is an example of the processing done by my music visualizer for iTunes on the Mac
more at www.fraktus.com/exo/exo_flickr.php
Or download it at fraktus.com/exo/eXo_12.dmg
The picture processed is downloaded automaticaly from the Flickr web site and is not mine, so it's a collective piece of art :-)
This one is more absract. There is a procedural texture in the background with several transparent cubes having different sizes and displaying a Flickr picture. It's creating surprising textures!
Revolve's photo exhibition launch at the Halles Saint Gery in downtown Brussels on July 1, 2014. In the presence of the City of Brussels, the Brussels Environment Agency (IBGE) and REScoop.
First Hacks/Hackers Meetup held at Atherton Studio at HPR. Great presentations by Ben Trevino, Jared Kuroiwa and Misa Maruyama.
Julia Kaganskiy (@juliaxgulia) organizes Arts, Culture and Technology meetups in NYC. This event on 27th April 2010 was on Data Mining & Visualization: www.meetup.com/Arts-Culture-and-Technology/calendar/13144...
Visualizing Patterns and Trends in Scientific Literature – What’s next? Chaomei Chen Many of us are interested in visualizing patterns and trends in scientific literature. It can be very exciting and revealing as well as challenging and frustrating. More often than not, a visualized ‘big picture’ of a scientific field invites more questions and more specific needs. Some may want to see more details; others may prefer a birds-eye view. There are quite a few unanswered questions. I’d like to line up a couple of them here. First of all, given any visualization of scientific literature, who would be able to understand what it is about? If there is such a thing as a typical viewer, what would be the viewer’s knowledge structure? The intended audience of the graphical message carried by the Pioneer spacecraft was aliens who would have competent knowledge of physics, at least as the way we understand it. If designers do not spell out their intent, where are the clues?
informationvisualization.typepad.com/sigvis/2005/02/visua...
www.connectedaction.net/2009/03/02/facebook-social-networ...
Here is a good example of an application of Bernie Hogan’s Facebook edgelist extractor. Alan Shussman used it on his own Facebook account and generated the following image: Alan Shussman's personal Facebook egonetwork visualization Alan Shussman's personal Facebook egonetwork visualization Alan used the NetworkX tool and python to build this image of his sub-groups in Facebook. It does work nicely to highlight the life-stage clusters of relationships that mostly stay inward focused, each school or work experience is a set of relationships that mostly link to themselves.
Browse 130 market data Tables and 54 Figures spread through 186 Pages and in-depth TOC on "Soldier Systems Market - Global Forecast to 2023
Latest update & sign-up for free access to PDF brochure
www.marketsandmarkets.com/requestsample.asp?id=137230260&...
flowingdata.com/2008/03/12/17-ways-to-visualize-the-twitt...
and
www.visualcomplexity.com/vc/project_details.cfm?id=594&am...
A way to visualize the Twitter universe. More visualizations on this website.
Akshay Java, from ebiquity group, used the Large Graph Layout (LGL) tool to visualize a large social network on Twitter. The top graph shown here was built using contacts from about 25,000 users. Notice that there is a link connecting two users if either one has the other as a friend and hence it is an undirected graph (of about 250,000 edges). Compare this to the bottom graph that is constructed using only users who are mutually acquainted. i.e. A knows B and also B knows A. As Akshay reveals in his post: "I find that visualizing such large graphs is quite a challenge and to glean meaningful information from it is even more difficult". However, he goes further in explaining that some insights can still be gained from this project. Akshay points out that a number of users seem to be trying to win a popularity contest of some sort, while a number of bloggers and (perhaps fake) celebrity profiles have a huge fan following in Twitter. He also mentions how the two graphs look very different on account of the fact that users with public profiles get a lot of followers whom they might not really know and would hence never add them as an acquaintance. But to really understand what the differences are one would need to look at the community structure and properties of the two graphs. ebiquity group has also explored the Twitter API in other projects [1] [2] in order to get a better understanding of the microblogging trend.
created by this applet: www.aharef.info/static/htmlgraph/
what the colors mean:
blue: for links (the A tag)
red: for tables (TABLE, TR and TD tags)
green: for the DIV tag
violet: for images (the IMG tag)
yellow: for forms (FORM, INPUT, TEXTAREA, SELECT and OPTION tags)
orange: for linebreaks and blockquotes (BR, P, and BLOCKQUOTE tags)
black: the HTML tag, the root node
gray: all other tags