Sponsored images from 
View allAll Photos Tagged Visualization
Viva apartments visualizations created for Adele Bates' interior design project in Brighton.
Software used: 3ds Max, Corona and Photoshop
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
JSMath is a JavaScript library that allows the display of complex mathematical expressions. LaTeX is a popular mathematical typesetting tool. Sage is compatible with both of them.
When taking photos, while the subject isn't ready, can lead to some very intriguing and interesting photos. Here for example, the hair and eyelashes were better emphasized than if a direct portrait were to be taken. A prism was also used in the bottom right corner to add a little bit of depth and effects into the photo.
Patrick van der Pijl: On January 4th 2011 Alex Osterwalder reinversed the business model of Facebook. On his blog he reconstructed together with his smart and loyal followers the model of Facebook. We thought it would be great to build on the work that has been done by visualizing this business model. More on www.businessmodelsinc.com - Illustration: Joeri Lefevre
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
Visualisation of emails received in a subfolder using the Java based Processing toolkit.
The long lines separate years, each row is a separate email address, the length of the green is the size of the email.
Email data exported from Outlook into Access then filtered into text doc for reading by Processing. Contact me if you want the script.
If you look deep in to the image, you can visualize alot of funny stuff from this image...give it a try! :)
What you see from distance in the image is a sand bank with small trees which is eventually going to be an island.
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
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
Paper at www.stat.columbia.edu/~gelman/research/published/signif4.pdf (PDF)
Let's say that a country, Lagutrop, wants to increase its PISA results and, before deciding on policy, the decision-makers want to know what works by running experiments or studies of intervention effectiveness. These studies compare two variables with similar intervention scales, say expenditure in computer-assisted learning (U) and expenditure in teacher selection and incentive systems (V).
In Study 1, data is collected measuring the effect of U and V (possibly with a lot of covariates). The parameter estimates for the effect of U and V are given by the two bell-curve-like curves on the left above.
Conclusion (as is traditionally presented): Lagutrop should invest in teacher selection and incentive systems, since computer-aided education has no significant effect.
Gelman and Stern problem 1: but the difference between the effects is itself non-significant! If significance is the criterion for disposing of U, then it should also be explained to the decision-makers that significance cannot be used to separate U from V. Specifically, policy-makers in Lagutrop should be told that the rejection of computer-aided education is based on a criterion that also suggests that computer-based education is as effective as teacher recruitment and incentives.
Meanwhile, another group of researchers run a single-variable study (Study 2) considering only the effects of spending money on teachers (in Lagutrop this study would probably have been done by teachers :-).
The results of Study 2 are then presented as supporting the conclusions of Study one, phrased as "Expenditure on teachers shows a significant effect on PISA scores in both studies."
Gelman and Stern problem 2: Studies 1 and 2 predict very different effect sizes for variable V; why the discrepancy? How can two parameter estimates that are significantly different from each other be considered corroboration?
My own take on this problem 2 is the following: suppose the policy-makers in Lagutrop have to decide how much to allocate to this PISA-improvement project, out of a budget that includes other considerations (national defense, jobs for the families and friends of the politicians, police, fire-fighters, etc.). Budgeting will require forecasting. Which of the parameter estimates for effect size will they use to build a forecasting model? Since the two estimates are significantly different, any attempt at aggregation would violate the basic meaning of that significance.
That's what we engineers call a serious execution problem.
(Reblogged at my personal blog.)
The last four years of my data from Facebook: gadgetwise.blogs.nytimes.com/2010/10/06/facebook-now-lets...
Visualized with GrandPerspective: grandperspectiv.sourceforge.net/
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
experimenting with post visualization, I split a city scene of Baltimore taken from the inner harbor and inserted a bloom from a tree in Missouri.
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
Edited NASA visualization of Antartica and part of Africa from 2005. A crop of this image is by far the most viewed image I've ever posted. Color/processing variant.
Image source: svs.gsfc.nasa.gov/vis/a000000/a003400/a003402/index.html
Original caption: In support of International Polar Year, this matching pair of images showing a global view of the Arctic and Antarctic were generated in poster-size resolution. Both images show the sea ice on September 21, 2005, the date at which the sea ice was at its minimum extent in the northern hemisphere. The color of the sea ice is derived from the AMSR-E 89 GHz brightness temperature while the extent of the sea ice was determined by the AMSR-E sea ice concentration. Over the continents, the terrain shows the average land cover for September, 2004. (See Blue Marble Next Generation) The global cloud cover shown was obtained from the original Blue Marble cloud data distributed in 2002. (See Blue Marble:Clouds) A matching star background is provided for each view. All images include transparency, allowing them to be composited on a background.
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
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
Sidebar on GSFC production from Digital Content Producer
(Sept, 2007)
digitalcontentproducer.com/hdhdv/depth/video_horizon/inde...
Visual Science Storytelling
Wade Sisler is the executive television producer at Goddard Space Flight Center in Maryland, and he has also worked at NASA HQ and the Ames Research Center in California. Trained in journalism at Baylor University and Scientific and Technical Still Photography at the Rochester Institute of Technology, he began working at NASA Ames in the mid ‘80s while finishing up his degree at RIT, and he says he never looked back. These days, Sisler is heavily involved in what he calls “Visual Science Storytelling.”
Sisler and other NASA Center employees around the nation use the discipline of television and video graphics to tell the story of projects, research, and missions created and managed by their particular center. The video, animation, and multimedia products they produce are for a variety of audiences both public and internally within the agency, and some of this content is also broadcast on NASA TV.
DCP: What brought you to NASA, and can you tell me a little about the background of video production at Goddard?
Sisler: For me, NASA was a great place because every time you turned over a rock, a mind-blowing story and often wonderful visual opportunity would crawl out. I liked that there were many new challenges and that many of the things I was to document had never been captured before. By the late ‘80s, I was dabbling in emerging multimedia, digital photography, and video, and while I hated the quality of the video image, I loved being able to go deeper into a story. Eventually, painfully, I made the shift to video and television just as the tools became affordable to small groups like the one we had at Ames. We felt lucky to be shooting on 3/4in. tape and were thrilled to eventually upgrade to Beta and then BetacamSP.
I transferred to NASA HQ in 1994 and then came to Goddard in 1997. At HQ, I worked on the IMAX films Mission to Mir and [Space Station 3D], and I also worked on projects with NASA TV.
How is Goddard different when it comes to the kinds of things you document with video?
When I came to Goddard, I found my true niche in scientific storytelling. Working here is a curious person's dream come true. The 9,000-plus scientists and engineers are literally changing the way humans see the universe and changing world we live in. NASA science provides insights into some of the most pressing problems and biggest questions of the day. Communicating the results of our missions is now woven into the DNA of our agency, and I think our team feels lucky to be working with an organization so passionate about sharing their story with the widest possible audience.
What are the main aspects of what you do?
There are really four main areas of challenge:
Visual science storytelling — translating complex stories with pictures, sound, and video
Creating or capturing absolutely compelling core content
Making that content widely available in multiple formats and multiple distribution channels
Doing all of the above very efficiently.
You've seen a lot of changes in the visual tools you use.
Sure. These days, the quality of the image is not an issue, of course. We now have end-to-end HD and shoot on Panasonic P2 and Varicam. A great deal of our work these days involves working with and directing animation and data visualization. Most of our important images are no longer shot with cameras, but are captured by satellites or are rendered in our visualizers' minds.
Interesting. And how do you share that content?
The biggest challenge we see is the fragmentation of the production/media world. We consider our customers to be a continuous spectrum of traditional print and broadcast media, web media portals, educators and students, museums, scientists, stakeholders — and, of course, the general public. The user community is fragmenting as the new media world carves up distribution channels into narrower and narrower slices. This fragmentation means that there are many more users creating many more products with our core content.
Can you describe the process of distribution?
Let's say we're producing material to illustrate the NASA mission objectives of a new kind of climate-observing satellite. Our work plan would usually call for creation of an animation illustrating the satellite at work. We would show it in action and illustrate how it works. We might also create contextual animation to help folks visualize the science behind the mission. Our producer will make sure to capture a few signature sequences that define a project.
These days, momentum has shifted to creating two- to three-minute reporter packages that can be used on places like NASA TV, web portals, and distributed via iTunes. The second part of our strategy is actively producing resource collections, which can be obtained via our fulfillment house or, increasingly, directly via online download.
Has HD and Internet streaming made inroads at Goddard?
HD has more than made inroads. Everything is HD. Even satellites are beginning to deliver HD. We've been shooting almost all HD for the past two years. It has been a little reach, but because we have such a high rate of reusing previous footage, it's been worth it. When the Solar Dynamics Observatory is launched next year, it will be sending down an HD image of the sun every second. Here comes the sun! We'll see all of the incoming space weather as never before. As far as web streaming goes, the new NASA portal will stream content and allow users to pull it down on demand. To get the uncompressed satellite footage and animations, producers will still need to go to the home centers like Goddard and JPL.
Can you tell me anything about Goddard’s work with stereo video?
We are working stereo video, but not with traditional cameras, for the most part. We do some work with the stereo pair of solar observatories. They produce essentially right-left eye images and we conducted our first press conference using the 3D images last April.
When NASA TV wants/needs programming from Goddard, is the footage sent via the WAN or via tape or hard drive, or another way?
We can send it via the WAN or directly via fiber. Goddard, like HQ and some of the other centers, is very connected to the various backbones. We conduct interviews with the networks and cable news outlet directly via the Bell Atlantic AVOC [a dedicated satellite two-way feed].
What can you tell me about the Scientific Visualization Studio at NASA’s Goddard Space Flight Center?
The Scientific Visualization Studio [SVS] turns raw satellite data into images. But this is much more than translating numbers to pixels. Frequently, these folks combine data from many satellites and sensors into a single comprehensive story. The mission of the SVS is to facilitate scientific inquiry and outreach within NASA programs through visualization. All the visualizations created by the SVS [currently totaling more than 2,700] are accessible to everyone through the website. More recent animations are provided as MPEG-1s and MPEG-2s. Some animations are available in high definition as well as standard NTSC format. Where possible, the original digital images used to make these animations have also been made accessible. Lastly, high- and low-resolution stills, created from the visualizations, are included, with previews for selective downloading [see svs.gsfc.nasa.gov].
Eric de Jong at NASA’s Jet Propulsion Lab is probably the unofficial leader on 3D within the agency. He has done quite a bit of 3D camera data viz work. Visit him at science.jpl.nasa.gov/people/deJong.
If there was one thing you’d like to share about digital multimedia content creation at Goddard, what would it be?
Our goal, and our mini slogan: One message, in many formats, through many channels, for many users!
—T.P.M