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Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
From Nexus: apps.facebook.com/_nexus_/
Connecticut on the left, Molecular on the bottom, WPI on top, and the Boston/Cambridge social scene on the right..
sent to my group www.flickr.com/groups/abc-visualized for the letter C: 1. Happy Furry weekend..., 2. Maiden Flight Concorde 002, 3. Colliding planes, 4. Untitled
I'd like to say hola! to my most frequent visitors, friends, family and not so friends but I really appreciate your kind support. I'm including the ones I know they silently come time to time. Also hello to my 4 well known spies who decided to choose the dark side of the force. I guess you're planning your holidays. I'll go to Mallorca and Ibiza soon. Well, this is not completely true yet but I need to visualize it to make it real! ;-D
This song always cheer me up. I don't know what it says... It sounds like Disney into me and I don't know why. I hope you're having a good time!
Listening...
www.goear.com/listen/f083f46/LDN-Lily-Allen
<3
Image from "Flight Thru Instruments," a 1945 US Navy pilot-training manual designed by the Graphic Engineering Staff at General Motors, under the direction of Harley Earl.
More explanation on the blog:
"Flight thru Instruments" and the Fine Art of Instructional Illustration
The University of Hawaiʻi at Mānoa’s Laboratory for Advanced Visualization & Applications (LAVA) was founded in January 1, 2014 by UH Mānoa Professor Jason Leigh. The mission of LAVA is to conduct research and development in big data visualization techniques, and to apply these techniques in cutting edge domain science, engineering, and training applications.
www.intersectionconsulting.comThis visual, inspired by Seth Godin, illustrates 5 pillars of marketing success: Vision, Objectives, Decision Making, Knowledge and Trust.
Graphed in this image are all the items that were featured on the front page then sold within the day, sorted into columns by price. It was generated from data spanning the last two weeks of September 2007 using a program written in Flash AS3.
Please view the original resolution.
Looks like there is a sweet spot at $15, as well as most of other multiples of $5. The sole item in the $0 column, was actually listed as $.20 and rounded down for the graph placement (also known as a P.I.F.).
www.etsy.com is a marketplace to buy and sell handmade goods and is a company I helped co-found in June 2005.
Visualisation de mon réseau social réalisé avec Nexus avec les contacts Facebook. rurl.org/r9i
2017 DownUnder Championships
Australia + New Zealand + USA
Griffith University Athletics Track
Gold Coast
Australia
Really interesting visualisation by Nexus: view interactive version
I've added some notes explaining the clusters. They're remarkably distinct.
* The left cluster is personal, the right cluster is work.
* There are 3 sub-clusters in Personal, and 4 sub-clusters in Work
* Jared connects both personal and work clusters. He connects with both Wheel/LBi (where he and I used to work) and Isotoma (where I currently work), and he and his wife became good friends of ours.
* Besides my wife and my brother, there are virtually no family members in the graph. They're not very wired.
* I've lost touch with nearly all people I knew in school, and most of those I knew in uni
* I tend to add only people I know fairly well in real life, and very rarely clients
Nexus also shows you what you have in common with people in your network (Interests and Groups), ordered by the number of similarities. In my cases mostly Interests since I don't tend to join Groups. (Interests are fuzzy and unreliable.) Interestingly, the person at the top of my similarity scale is one of the outliers, Mary, whom I only know through Flickr.
Would love to see something like this for Twitter. TwitterAnalyzer is similar, but does not do the same kind of clustering. Also want this for Linkedin and Flickr
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA
This is a Social network anlysis from www.linkedinlabs.com/inmaps of my LinkedIn contacts. The color coding corresponds to different groups that I know, and how the tool classifies them. (I will say that it is remarkably correct)
LinkedIN20120610a
PROJECT:Jinhui Park
DESIGNED BY SCDRI
RENDERED BY FRONTOP
Frontop creates 3d rendering, architectural rendering, architectural visualization and architectural animation for architects, designers, real estate developers and much more.
For a nice comparison, this is a graph originally done when Etsy was 2 months old. It shows all registered Etsy users with avatars on August 11, 2005. Ordered from top left to bottom right by date of registration.
See the same visualization for the month of October 2007.
Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
CMS utilizes a distributed infrastructure of computing centers to provide access to data stored on disk only at Tier-2 centers and tape with disk caches at Tier-1 centers. Attached are CPU resources for organized processing and analysis. Data is organized in datasets which consist of files grouped in blocks for performance reasons. CMS uses it's data transfer system PhEDEx, to transfer datasets from site to site and its data bookkeeping service DBS to track location and metadata. Integrated over the whole system, even in the first year of data taking, the available disk storage approaches 10 petabytes of space. Maintaining consistency between the data bookkeeping service, the data transfer system, and physical storage is an important operational task which guarantees uninterrupted data availability.
Good grief...!!! This reminds me of the walls of my room growing up. We weren't allowed to put posters up, but I won a B&W poster of Tarzan at the State Fair and it was all over from there. By the time I moved out, my room was one giant Vision Board with the walls and ceiling completely covered!
I did my first Vision Board when I was 10. You know me, I still have it somewhere. It is all about women's fashion a la 1970 and is on purple construction paper. This was before I knew I would have a purple room and spend many years of my career in women's and men's fashion. So there must be something to the concept of a Vision Board and the achievement of one's future dreams.
Now, my Vision Board isn't so much about having material things. That's ok and I already have enough things. It's more about how I aspire to be and the time I would like to have to do it all.
In the instructions, they say to not worry about being artistic. How do you tell an artistic person to not be artistic...lol? And they say to put it in a place where you can see it often. So there you have it!
Now, I've got to go clean my room. Or NOT!!!
Thank you, Joe for letting me use the pic of me. One reason I love this pic is because it was taken in front of the statue of Columbus. Someone who had a definite vision of where he wanted to go. . .
Please!! NO Awards or Large Graphics...Group Buddy Icons are OK. Thank You!
© CPMcGann. All rights reserved. If you are interested in using my images, please contact me first.
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA
sent to my group www.flickr.com/groups/abc-visualized for the letter B: 1. big small, 2. Boat floating on clouds, 3. harmony . . ., 4. Playin_de_Blues
You can see what remains of a ledge where the Freemont people likely stood a 1,000 years ago to carve the figures in the stone. Sadly, the ledge has lasted to current times so it enables people to vandalize the ancient symbols.
Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
After seeing Cooper Smith's visualizations of data from runners in New York City, I wanted to see what similar data sets would look like for other cities. Nike+ doesn't have public GPS logs, but MapMyRun does, if you are willing to spend several hours clicking through search results to hit the "Download" buttons, so that's what I did to get the tracks for these 771 runs (from June 13 through August 9) in San Francisco.
As Open Source Planning has pointed out, uploaded runs come from a fairly small, self-selected group of people, the most obvious result of which is the total absence of the southeastern corner of the city from this map. It is also a very self-conscious process, so it is biased toward intentional, and often intentionally difficult, trips made for their own sake, and away from the repetitive patterns of everyday life.
Unfortunately the MapMyRun tracklogs do not have date and time stamps, so it is not possible to do the time of day, pace, and interruption analyses that Cooper Smith did. I should have done direction of travel, though.
Kunal Anand was kind enough to do some crazy ass Python/Processing hack to create a cluster of all my tags and how they interoperate. Looks cool and cloudy.
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA