Archive for the ‘visualization’ Category
Workshop: Telling Stories With Data
The Telling Stories With Data session was a continuation of last year’s session, largely inspired by the Edward Segel and Jeffrey Heer paper; “Narrative Visualization: Telling Stories with Data.”
Steve Drucker from Microsoft Research talked about his rich interactive narrative player work. The tool uses XML to set up a queue of keyframes with audio narration. It supports audio narration and multimedia embedding.
Wesley Willet talked about supporting ad-hoc storytelling in social media. He raised several technical issues, including the need for interactive visualization state encoding in URLs. This would allow people to link to a specific state in the visualization, and share that state over social media.
Jerome Cukier talked about adding personal connections to visualizations to help audience engagement. He also discussed the importance of providing interaction that lets users feel like they are exploring the dataset and coming to their own conclusions. A significant take- away quote Jerome had is “Trust is not really an exact science.”
Sunah Suh framed a discussion about the impact of culture on visualization and visualization on culture. She discussed the multiple forms of literacy beyond just natural language, addressing issues of statistical literacy as well as visual. She raised the point that visualization does not just reflect and rely on societal norms, it also reinforces them. One example she gave was the pink and blue color coding in Baby Name Voyager reinforcing a binary gender concept.
The takeaways from the first half of the session dealt with technical issues of platforms and tools to support narratives, as well as some of the social issues going on in narrative visualizations. Both of these are important issues as narrative visualization finds its place in culture. The necessary tools must be developed to help narrative visualization become ubiquitous, but also there are social issues to be addressed as people come to terms with the new media.
These notes were transcribed by Lane Harrison (@laneharrison) and Drew Skau(@seeingstructure). They are both graduate students at UNCC. Thanks guys!! There were other excellent speakers who presented, but Drew and Lane were presenting in an adjoining session.
The annual IEEE Visualization, IEEE Information Visualization and IEEE Visual Analytics Science and Technology conferences – together known as IEEE Visweek will be held in Providence, RI from October 23rd to October 28th.The detailed conference program is spectacular and can be downloaded here.Some of the new events this year are under the Professional’s Compasscategory. It includes a Blind date lunch (where one can meet some researcher they have never met and learn about each others research), Meet the Editors (where one can meet editors from the top graphics and visualization journals), Lunch with the Leaders session (an opportunity to meet famous researchers in the field) and Meet the faculty/postdoc candidates (especially geared towards individuals looking for a postdoctoral position or a faculty position). I think this is an excellent idea and hope that the event is a hit at the conference.I am also eagerly looking forward towards the two collocated symposia – IEEE Biological Data Visualization (popularly known as biovis) and IEEE LDAV (Large data analysis and visualization). Their excellent programs are out and I’d encourage you to take a look at them.
The tutorials this year look great and I am particularly looking forward to the tutorial on Perception and Cognition for Visualization, Visual Data Analysis and Computer Graphics by Bernice Rogowitz. Here is an outline for the tutorial that can be found on her website. She was one of the first people to recommend that people STOP using the rainbow color map.
The telling stories with data workshop too looks great and will be a continuation of the great tutorial held by the same group last year. I am eagerly looking forward to it.
Apart from this are the excellent papers that will be presented at the conference. I shall write another post about the ones I am particularly looking forward to. With so many exciting events going on, it almost seems like a crime to have all of them happening in the span of a few days.
I shall definitely be blogging about the event as much as I can. You can also follow me on twitter, which will have more real time tweets than the blog which will distil a days worth of information into a post.
Let me know if you are going to be around and I’ll be happy to talk to you.
Data visualization is being used for detecting fraud, especially with respect to wire and credit card transactions. Work done at the Charlotte Visualization Center at UNC Charlotte provides some interesting insights into fraud detection. This work was conducted in collaboration with the Bank of America.In the following paper they highlight four visualization techniques that allow for fraud detection.
Scalable and Interactive Visual Analysis of Financial Wire Transactions for Fraud Detection, Remco Chang, Alvin Lee, Mohammad Ghoniem, Robert Kosara, William Ribarsky, Jing Yang, Evan Suma, Caroline Ziemkiewicz, Daniel Kern, Agus Sudjianto, Journal of Information Visualization (IVS).
Search by example: Find accounts with transactions/activity similar to the current account being monitored.
Strings and beads: A line graph based visualization that shows critical events as ‘beads’ on the graph. The use of a log scale for the y-axis is a neat idea and probably allows for improved exploration.
Keyword graph: A graph visualization showing keyword similarity This paper was based on previous work done by the same group titled Wirevis. I would encourage interested readers in reading the original paper as well as the previous paper (Wirevis).
- It is a web-based solution that allows interactive exploration of data for fraud detection.
- Can read a wide variety of file formats (excel/access databases).
- Allows interaction with visualizations such as node-link diagrams, bar charts etc.
You can check out a 10-min video on their website at http://www.centrifugesystems.com/shadowbox/libraries/mediaplayer/Centrifuge-1.8-for-Banking-Fraud-Analysis.flv. As per the company website, it has been used to detect fraud in Bulgaria called the “Bulgarian Money Mule ring”. Seems like a step in the right direction. It would be interesting to see, if they could save and share workspaces for collaborative exploration of data. With their web-based framework, it would make it particularly interesting for investigators located at different locations to immediately access and interact with the current state of the visualization.
Any other companies, products, research papers that you may have heard of that I missed?
Lately, I have been collecting links to videos of talks related to Data Visualization. I found multiple talks for some people and so have categorized them accordingly. I have also tried to provide some context to the individual/group.
I think the first TED talk by Hans Rosling (@hansrosling) got a lot of media attention and made people sit up and appreciate the power of ‘narrative visualization’. He almost make it look like a sport with him serving as the role of a commentator. The title on TED’s website for the talk is “the best stats you’ve ever seen“. I am not sure about that, but it is a very entertaining talk.
It was followed up by an interesting study by information visualization researchers George Robertson, Roland Fernandez, Danyel Fisher, Bongshin Lee and John Stasko in the Infovis 2008 paper titled “Effectiveness of Animation in Trend Visualization.” Here is an interesting excerpt from the abstract of the paper:
Results indicate that trend animation can be challenging to use even for presentations; while it is the fastest technique for presentation and participants find it enjoyable and exciting, it does lead to many participant errors. Animation is the least effective form for analysis; both static depictions of trends are significantly faster than animation, and the small multiples display is more accurate.
Fernanda Viégas and Martin Wattenberg (@wattenberg) (previously at IBM Research) have brought visualization to the masses in through IBM Many Eyes. They have recently started a new venture called FlowingMedia. Here are some links to their talks:
- TEDxSP 2009 - Fernanda Viégas (in Portuguese with english subtitles)
- Stanford CS Department – Democratizing Visualization (wmv)
Manuel Lima (@mslima) of visualcomplexity.com gave an interesting talk at Made by Many. His talk titled Network Visualization in an Age of Interconnectedness was not only an excellent talk, but ended up starting quite a passionate debate which led to Manuel writing a post titled Information Visualization Manifesto. I urge you to read the post and look at the interesting perspectives that infovis experts in the field had to Manuel’s manifesto. Manuel gave another interesting talk at the Creativity and Technology (CaT) 2009: Information Visualization.
Aaron Koblin (@aaronkoblin) has been involved with creating innovative and evocative data visualization pieces such as the New York Talk Exchange, Radiohead’s House of Cards music video (You can see Aaron in the “Making of House of Cards” video), the very entertaining ‘Bicycle built for 2000‘ project and many others.
Making of House of Cards
Links to a couple of Aaron’s talks are below:
Tom Wujec is a fellow at Autodesk. His talk on 3 ways the brain creates meaning provides an amazing insight into our brain. He addresses issues related to why data visualization works and how the brain visualizes data.
Jeff Heer has developed information visualization tools that can be used by developers around the world for creating interactive visualizations of their own data. He is the authors of Prefuse, Flare (Check out the excellent demos) and most recently, Protovis (many great examples online). Lately, he has published an informative articles in the ACM Queue titled A tour through the visualization zoo - Jeffrey Heer, Michael Bostock, Vadim Ogievetsky. He does a great job interviewing Fernanda Viegas and Martin Wattenberg in the ACM Queue. A talk by him at the Stanford HCI seminar can be found here (html link, wmv).
Nicholas Christakis presents a very fascinating talk where he used social data visualization to explore the influence of social networks – “The hidden influence of social networks.” In his talk he says that spreading of obesity is due to your social network. Smoking and even divorce can be linked to the company you keep.
Please let me know if I have missed any interesting data visualization talks that are available online and I will be happy to update the post.
As a new parent, I have always been guilty of driving a compact car when everyone around me keeps telling me that even though SUV’s are bad for the environment they are so much safer in case of an accident. I cringed a bit at every such discussion but thought that maybe they had a point.
But then I thought why not use data visualization to get to the bottom of this and find out what the truth is. Let me preface this by saying that this is my first attempt at visualizing the data I could find for free and any visualization suggestions or data sources that you are aware of will be greatly appreciated.
[Note: No fancy visualizations here :) Only good old bar graphs]
Step 1 – Type of the car vs Fatalities
I first wanted to find out what is the breakdown of car crashes as compared to the type of car. I found that there is extensive data (see data sources below) about car crashes and fatalities. I decided to use fatalities as a measure of how ‘safe’ the car is and so this graph shows the type of car as compared to the fatalities in 2008. I was sad to see that ‘Passenger cars’ were ranked first but happy to see that ‘Light trucks’ were pretty high up too. Minivans, Compact utility and Large Utility vehicles had far fewer fatalities and I was worrying whether my worst fears (SUV/Minivan = safer) were coming true.
Step 2 – Sales for each type of car
But then I thought that the number of accidents obviously is very dependent on the number of cars that get sold per year and if more passenger cars were getting sold, then more of them would be in a fatal accident thus giving it a higher number. So I found out what the car sale numbers were for 2008 (see data source below) and decided to plot that.
Step 3 – Comparing the Fatalities/Sales ratio
Then the next obvious thing to do was to compute a ratio of the number of fatal accident per type of car with the number of cars sold for that type in a year. On computing the ratio, I found something very interesting. Sorting the graph based on this ratio, I found that Compact Utility vehicles had the highest ratio of fatal accidents to sales. If you look at the first graph, you will see that the compact utility vehicles do not have a large amount of fatal accidents to begin with, but then when that number is divided by the total amount of compact utility vehicles sold, we find an interesting insight (much to my relief and joy).
Passenger cars have a lower ratio than Compact utility vehicles, Large utility vehicles and Light trucks. :)
Anyone who has used Tableau has probably already guessed that all these visualizations were created using Tableau Software and so I visualized the Ratio, Fatal Accidents, Sales all in one image. It shows clearly how compact utility vehicles have a high ratio even though trucks and passenger cars have higher fatalities and more cars of those types were sold.
My current data sources are (Please let me know if you are aware of better ones):
Fatality analysis reporting system – http://www-fars.nhtsa.dot.gov/States/StatesCrashesAndAllVictims.aspx
WSJ – Car sales for the year so far - http://online.wsj.com/mdc/public/page/2_3022-autosales.html
InfoVis (Information Visualization) 2009 is an integral part of the Annual VisWeek conference. This year the VisWeek conference will be held in Atlantic city, NJ from October 11th-16th. In the next few posts, I shall post my views on things to look out for in each of the tracks at the VisWeek conference: VAST, Vis and Infovis. Here are some exciting talks/panels/workshops/tutorials that I’m looking forward to at InfoVis this year (Links and other material shall be updated as material becomes available):
Collaborative Visualization on Interactive Surfaces (CoVIS)
Organizers: Petra Isenberg, Michael Sedlmair, Dominikus Baur,
Tobias Isenberg, Andreas Butz
Visualization and Analysis Using VisIt
Organizer: Hank Childs
Exploring Design Decisions for Effective Information Visualization
Organizers: Jo Wood, Jason Dykes, Aidan Slingsby
InfoVis Best Paper Award
ABySS-Explorer: Visualizing Genome Sequence Assemblies
Cydney B. Nielsen, Shaun D. Jackman, Inanç Birol, Steven J.M. Jones
InfoVis Best Paper Award
Mapping Text with Phrase Nets
Frank van Ham, Martin Wattenberg, Fernanda B. Viégas
InfoVis Honorable Mention
MizBee: A Multiscale Synteny Browser
Miriah Meyer, Tamara Munzner, Hanspeter Pfister
InfoVis Honorable Mention
Configuring Hierarchical Layouts to Address Research Questions
Aidan Slingsby, Jason Dykes, Jo Wood
InfoVis Honorable Mention
SellTrend: Inter-Attribute Visual Analysis of Temporal Transaction
Data, Zhicheng Liu, John Stasko, Timothy Sullivan
Spatiotemporal Analysis of Sensor Logs using Growth Ring Maps
Peter Bak, Florian Mansmann, Halldor Janetzko, Daniel A. Keim
A Nested Model for Visualization Design and Validation
“Search, Show Context, Expand on Demand”: Supporting Large Graph Exploration with Degree-of-Interest
Frank van Ham, Adam Perer
A Comparison of User-Generated and Automatic Graph Layouts,
Tim Dwyer, Bongshin Lee, Danyel Fisher, Kori Inkpen Quinn, Petra Isenberg, George Robertson, Chris North
Visualizing Social Photos on a Hasse Diagram for Eliciting
Relations and Indexing New Photos, Michel Crampes, Jeremy de Oliveira-Kumar, Sylvie Ranwez, Jean Villerd
Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations
Christopher Collins, Gerald Penn, Sheelagh Carpendale
Temporal Summaries: Supporting Temporal Categorical Searching, Aggregation and Comparison
Taowei David Wang, Catherine Plaisant, Ben Shneiderman, Neil Spring, David Roseman, Greg Marchand, Vikramjit Mukherjee, Mark Smith
Harnessing the Web Information Ecosystem with Wiki-based Visualization Dashboards
SpicyNodes: Radial Layout Authoring for the General Public
Michael Douma, Grzegorz Ligierko, Ovidiu Ancuta, Pavel Gritsai, Sean Liu
code swarm: A Design Study in Organic Software Visualization
Michael Ogawa, Kwan-Liu Ma
Protovis: A Graphical Toolkit for Visualization
Michael Bostock, Jeffrey Heer
Participatory Visualization with Wordle
Fernanda B. Viégas, Martin Wattenberg, Jonathan Feinberg
Capstone: Visual aids: Use of Paintings and Photography for Lighting in the Theater
Speaker: Brian MacDevitt, Broadway Lighting Designer
The IEEE Transactions on Visualization and Computer Graphics journal completed 15 years this month and in the editorial, the 10 most cited papers in the last 15 years have been mentioned. Some of them are survey papers and some are classics. These papers have received between 550-250 citations in the past 15 years.
Here are the papers (in no particular order):
- I. Herman, G. Melançon, and M.S. Marshall, “Graph Visualization and Navigation in Information Visualization: A Survey,” IEEE Trans. Visualization and Computer Graphics, vol. 6, no. 1, pp. 24-43,Jan.-Mar. 2000.
- M. Alexa, J. Behr, D. Cohen-Or, S. Fleishman, D. Levin and C.T. Silva, “Computing and Rendering Point Set Surfaces,” IEEE Trans. Visualization and Computer Graphics, vol. 9, no. 1, pp. 3-15,Jan.-Mar. 2003.
- J.T. Klosowski, M. Held, J.S.B. Mitchell, H. Sowizral and K. Zikan, “Efficient Collision Detection Using Bounding Volume Hierarchies of k-DOPs,” IEEE Trans. Visualization and Computer Graphics, vol. 4, no. 1, pp. 21-36,Jan.-Mar. 1998.
- J. Rossignac, “Edgebreaker: Connectivity Compression for Triangle Meshes,” IEEE Trans. Visualization and Computer Graphics, vol. 5, no. 1, pp. 47-61,Jan.-Mar. 1999. GVU Tech Report.
- D.A. Keim, “Information Visualization and Visual Data Mining,” IEEE Trans. Visualization and Computer Graphics, vol. 7, no. 1, pp. 1-8,Jan.-Mar. 2002.
- N. Max, “Optical Models for Direct Volume Rendering,” IEEE Trans. Visualization and Computer Graphics, vol. 1, no. 2, pp. 99-108,June 1995.
- P.M. Hubbard, “Collision Detection for Interactive Graphics Applications,” IEEE Trans. Visualization and Computer Graphics, vol. 1, no. 3, pp. 218-230,Sept. 1995.
- S. Lee, G. Wolberg, and S.Y. Shin, “Scattered Data Interpolation with Multilevel B-Splines,” IEEE Trans. Visualization and Computer Graphics, vol. 3, no. 3, pp. 228-244,July-Sept. 1997.
- G.W. Larson, H. Rushmeier, and C. Piatko, “A Visibility Matching Tone Reproduction Operator for High Dynamic Range Scenes,” IEEE Trans. Visualization and Computer Graphics, vol. 3, no. 4, pp. 291-306,Oct.-Dec. 1997.
- K. Perlin, “Real Time Responsive Animation with Personality,” IEEE Trans. Visualization and Computer Graphics, vol. 1, no. 1, pp. 5-15,Mar. 1995.
Please feel free to add any other TVCG papers that have influenced your work significantly. Congrats TVCG and all the people involved with it!