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• Top 10 FlowingData Posts for 2007

  Posted Dec 31, 2007 to Announcements / Add your comment

  It's been a little over six months since I put up my first FlowingData post about creating effective visualization. Going through the archive, I'm amazed by how much this blog has developed and more importantly, by the people I've found who have many of the same academic interests that I do. For that, I'm extremely grateful.

  I'm also pretty impressed with how consistent I've been with the posts, because to be honest, I wasn't sure if I'd be able to keep it up when I first started. Had I known about all of the interesting data visualization work and research going on, I wouldn't have had such sour thoughts. Now I know better, and I hope others are benefiting.

  So here we are -- the top 10 most viewed posts for 2007:

  1. Three Designers, a Statistician, and Migration Inflows Data
  2. What is the Best Way to Learn Flash/Actionscript for Data Visualization?
  3. News Flowing Through Moveable Type at The New York Times Building
  4. Visualizar Showcase Officially Opened at Medialab
  5. Yahoo Charts Control Library Now Available
  6. Sharing Personal Data to Push Social Data Analysis
  7. Netflix Prize Dataset Visualization
  8. 100 Reasons You Should Be Interested in, Want to Share, and Get Excited About Data
  9. Bars as an Alternative to Bubble Charts
  10. Use Flare Visualization Toolkit to Build Interactive Viz for the Web

  Happy new year! See you in 2008.

• Sit Back and Relax with Casual Information Visualization

  Posted Dec 28, 2007 to Artistic Visualization / 2 comments

  

  

  

  Zachary Pousman et al. write in their paper Casual Information Visualization: Depictions of Data in Everyday Life

  Information visualization has often focused on providing deep insight for expert user populations and on techniques for amplifying cognition through complicated interactive visual models. This paper proposes a new subdomain for infovis research that complements the focus on analytic tasks and expert use. Instead of work-related and analytically driven infovis, we propose Casual Information Visualization (or Casual Infovis) as a complement to more traditional infovis domains. Traditional infovis systems, techniques, and methods do not easily lend themselves to the broad range of user populations, from expert to novices, or from work tasks to more everyday situations.

  At the paper's roots, it goes onto cover the edge cases in infovis -- ambient, social, and artistic infovis. The three are perhaps not what we consider traditional infovis in that we're not going to sit down with them for a couple of hours to gain some kind of insight. Instead, ambient, social, and artistic viz are displayed constantly and the casual observer gets something other than analytic insight. Causual infovis draws upon awareness, social, and reflective insight. I won't go into the details of each type of insight. You can just read the paper.

  Catering to a Wider Audience

  This paper brings up some good points about traditional information visualization and how the edge cases of infovis (ambient, social, and artistic) pose different design problems -- mostly which come from trying to display information in a way that everyone can understand.

  My one criticism is that the authors don't seem to place much faith in the user. The authors mention that users may not be experts in understanding complicated graphs and charts (which is kind of true), so casual infovis can only show a small number of attributes. I like to think though that instead of dumbing down the vis, we should work on improving data literacy and in turn, should expect the user to grow more accustomed to more complex visualization.

• Using Data to Find Likely Crime Spots

  Posted Dec 27, 2007 to Statistics / 2 comments

  I stumbled across this article about Aili Malm, a GIS specialist (I think) who uses social network analysis to find the most probably locations of organized crime.

  "I look at where organized crime groups are located and I study how these groups are linked to one another," she explained. "I can chart their cell phone use or e-mail communication or with whom they co-offend. Based on these connections, I try to isolate the important players. Then I take the social and make it spatial. I look at individuals important to the criminal network and map where they live and where they commit their crimes."

  It's just like that show Numb3rs on CBS. Albeit, math and statistics is a bit glorified on the show, but hey, at least it's loosely based on reality.

• Ho, ho, ho, Meeerrrrry Christmas!

  Posted Dec 24, 2007 to Announcements / Add your comment

  Merry Christmas Bedford Falls! Merry Christmas you old Savings and Loan! Merry Christmas Mr. Potter! Merry Christmas! Gosh, I love that movie. I watch it every year, and it never gets old. That scene where he comes home so happy to be alive, his children are hanging off of him, and he's embracing his wife... wonderful.

  On that note, posts here on FlowingData will be sparse through January 1 as I buckle down and focus on relaxing and having fun. I can't wait to see what Santa brings me. I am going to make sure I leave him extra cookies and a big glass of milk. I suggest you do the same. Santa wasn't so nice last year. He gave me a pair of used socks, a half-eaten candy cane, and a note that asked, "Where are my cookies and milk?" I am sorry Santa. It will never happen again.

  Merry Christmas and have a happy new year!

• Download Detailed Baseball Statistics from the DataBank

  Posted Dec 21, 2007 to Data Sources / 3 comments

  

  Baseball (or all sports for that matter) statistics are all over the place. You can easily find data for pretty much whatever sport and for whichever player you want at any given time. The problem is that if you want to download all of the data at once, you usually have to write a script and do some parsing. Who wants to do that? I don't.

  Continue Reading

• Names Mentioned in Debates by Major Presidential Candidates

  Posted Dec 20, 2007 to Network Visualization / 3 comments

  

  Jonathan Corum and Farhana Hossain created a network visualization that shows readers who has spoken about who in presidential debates. Scroll over each candidate name to isolate the connections; important/interesting points are highlighted. Candidates are colored blue and red for their respective political parties.

  There are three main things that this thing shows -- who has spoken about who (lines), who has been talking the most (circle segments), and finally, attention by party (red and blue). In usual fashion, The New York Times churns out another beautiful graphic. Not only is the visualization attractive, but unlike so many network diagrams before it, this graphic is also useful and informative.