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):

Workshops:
Collaborative Visualization on Interactive Surfaces (CoVIS)
Organizers: Petra Isenberg, Michael Sedlmair, Dominikus Baur,
Tobias Isenberg, Andreas Butz

Tutorials:
Visualization and Analysis Using VisIt
Organizer: Hank Childs

Exploring Design Decisions for Effective Information Visualization
Organizers: Jo Wood, Jason Dykes, Aidan Slingsby

Keynote: Visual Thinking and Visual Thinking Tools
Speaker: Colin Ware, Data Visualization Research Lab, University of New Hampshire

Panels:
Changing the World with Visualization
Organizer: Robert Kosara
Panelists: Sarah Cohen, Jerome Cukier, Martin Wattenberg

Papers:
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
Tamara Munzner

“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

Lark: Coordinating Co-located Collaboration with Information Visualization – YouTube Video – Paper link
Matthew Tobiasz, Petra Isenberg, Sheelagh Carpendale

Harnessing the Web Information Ecosystem with Wiki-based Visualization Dashboards
Matt McKeon

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

VAST is the Visual Analytics track at 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/sessions that I’m looking forward to this year (Links and other material shall be updated as soon as the papers are available):

Interactive Visual Clustering of Large Collections of Trajectories,
Gennady Andrienko, Natalia Andrienko, Salvatore Rinzivillo, Mirco Nanni, Dino Pedreschi, Fosca Giannotti

A Framework for Uncertainty-Aware Visual Analytics
Carlos D. Correa, Yu-Hsuan Chan, Kwan-Liu Ma

Parallel Tag Clouds to Explore and Analyze Faceted Text Corpora (YouTube Video)
Christopher Collins, Fernanda B. Viégas, Martin Wattenberg

Describing Story Evolution from Dynamic Information Streams
Stuart Rose, Scott Butner, Wendy Cowley, Michelle Gregory, Julia Walker

Evaluating Visual Analytics Systems for Investigative Analysis: Deriving Design Principles from a Case Study
Youn-ah Kang, Carsten Görg, John Stasko

Visual Analysis of Graphs with Multiple Connected Components
Tatiana von Landesberger, Melanie Görner, Tobias Schreck

VAST Best Paper Award: Iterative Integration of Visual Insights during Patent Search and Analysis
Steffen Koch, Harald Bosch, Mark Giereth, Thomas Ertl

FinVis: Applied Visual Analytics for Personal Financial Planning
Stephen Rudolph, Anya Savikhin, David S. Ebert

Visual Opinion Analysis of Customer Feedback Data
Daniela Oelke, Ming Hao, Christian Rohrdantz, Daniel A. Keim, Umeshwar Dayal, Lars-Erik Haug, Halldór Janetzko

VAST Capstone Panel
How Interactive Visualization Can Assist Investigative Analysis: Views and Perspectives from Domain Experts
Organizer: John Stasko
Panelists: Sarah Cohen, Lawrence Hunter, Joe Parry

Are you planning to come by to the VisWeek conference? Is so, which sessions are you interested in?

In this post, I focus on the use of visualization in conveying information regarding the environment, pollution, population effects on the planet and similar issues. The visualizations are particularly powerful and make us realize how much of an impact we have on the world.

• Breathing Earth is a wonderful visualization that shows a visual representation of the amount of CO2 that is being produced every second. Additionally, based on the statistics there is a neat visual representation of number of births and deaths per second. This image is just a snapshot of the ever evolving visualization. Check out the really eye-opening visualization at http://www.breathingearth.net/

• The Global Footprint Network is an amazing resource that provides information about our footprint on the planet. Other than the excellent scientific resources, they have a quiz that lets you know your carbon footprint at the end. The quiz can be taken at   http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/. Here’s a screenshot from the quiz which is really well done. 

• The Visualization Sciences Group (The company that maintains OpenInventor among other things) has a video showing the amazing capabilities of their visualization software - Avizo Green. The video can be seen at http://www.mc3dviz.com/video/player.php?vfile=avizo/AVIZO_GREEN_mercury640×360.flv. Here is a screenshot from the amazing video.  Hedgehogs when visualized over time convey the wind velocity so effectively.

• A research paper by Wood et al. discusses a web-based solution to visualize environmental data. The snapshot below shows a histogram View of Ozone from 3 sites in London - Jason Wood, Ken Brodlie and Helen Wright, Visualization over the World Wide Web and its application to environmental data, Proceedings of IEEE Visualization 1996 Conference, edited by R.Yagel and G.M. Nielson, pp 81–86, ACM Press. ISBN 0-89791-864-9. 

• National Public Radio (NPR) had a very informative piece on Visualizing The U.S. Electric Grid - Here are some screenshots from the story. I wonder if they could have picked better visualizations to show the ’sources of power’.

It is a bit hard to visualize the differences in power generating capabilities of various states since the saturation is mapped to a value. Considering there are only a few different values, using different colors may have been a good idea. Any other thoughts on what they could have used to represent this data more effectively?

Here’s another visual representation of the wind energy sources.

What seemed most interesting to me is how much the US is dependent on coal power as compared to wind. I hope with the new administration’s initiatives for green energy, we will see a change in the near future.

• Visualizing rainfall in Australia –  You can interact with the website to pick different visualizations. They seem to be pre-generated though. Here is a screenshot of one of the visualizations

• NY Times article discussing the growing interest in visualizing and drawing attention to the climate change problem through visualization.

• Globalwarmingart.com is a website dedicated to drawing attention the problem of climate change through the use of visualizations and infographics. Shown here is the now (in)famous ‘embers’ graph that the Intergovernmental Panel on Climate Change (IPCC) did NOT include in their report on climate change, since some scientists thought that the visualization “was too unnerving.” Here is the actual figure and its discussion on NYTimes dotEarth blog - http://dotearth.blogs.nytimes.com/2009/02/23/warming-embers-burning-brighter/

• Climate Central – a non-profit organization has some excellent resources that are meant for media and for raising public awareness about the topic of climate change. You can some excellent video as http://www.climatecentral.org/video/. In their own words

Climate Central is an accessible one-stop source for timely, relevant, high-quality climate information through a variety of channels, targeting the media and leaders in business, government, and religion.

• WaterLIFE is a wonderfully informative website that provides information about water. It contains videos, photographs and visualizations that draw your attention to the various factors affecting water. Its a really amazing site and the snapshot below does not do it justice. Anyway, check it out at http://waterlife.nfb.ca/. Here’s a snapshot from their website

Have you seen any other visualization/website that has been used to communicate, inform, educate people about the issues surrounding environmental factors? If so, please feel free to add them in the comments section.

The VisWeek 2009 website has been update with a list of all the accepted papers for this year.

The list can be found at

Vis Papers: http://vis.computer.org/VisWeek2009/vis/sessions_papers.html

InfoVis Papers: http://vis.computer.org/VisWeek2009/infovis/sessions_papers.html

VAST Papers: http://vis.computer.org/VisWeek2009/vast/sessions_papers.html

I am particularly happy to see that Vis and InfoVis will overlap slightly this year. It will showcase the best work from both the fields and allow for researchers to interact and form new collaborations. There seem to be some really interesting papers, workshops and tutorials. Other new features this year are the Discovery Exhibition and the Forum on Geometric Aspects of Machine Learning and Visual Analytics. Looking forward to an interesting conference in Atlantic City, NJ.

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):

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. N. Max, “Optical Models for Direct Volume Rendering,” IEEE Trans. Visualization and Computer Graphics, vol. 1, no. 2, pp. 99-108,June 1995.
7. P.M. Hubbard, “Collision Detection for Interactive Graphics Applications,” IEEE Trans. Visualization and Computer Graphics, vol. 1, no. 3, pp. 218-230,Sept. 1995.
8. 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.
9. 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.
10. 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!

The Eurovis 2009 conference concluded a few days ago in Berlin. Here are some of the papers that I found interesting. Links for all the papers are not available yet, but I shall update the post as and when I find them. Here is the whole list of accepted eurovis 2009 papers.

The keynote talk was given by Pat Hanrahan who is known to give very insightful and thought provoking keynote and capstone talks. This keynote talk was titled Systems of Thought. You can also take a look at his slides from other talks on this website http://graphics.stanford.edu/~hanrahan/

This year at the conference, they awarded 3 best paper awards. Congratulations to the authors of the papers! These are the ‘best paper award winners’:

Visualisation of Sensor Data from Animal Movement
Edward Grundy, Mark W. Jones, Robert S. Laramee, Rory P. Wilson and Emily L.C. Shepard – In this paper they present a unique way of visualization data obtained from sensors attached to animals as they move around the world. Animals such as the cormorant, sea turtles and such were tagged with tri axial accelerometers and tracked through time.

On Visualization and Reconstruction from Non-Uniform Point Sets using B-Splines
Erald Vuçini, Torsten Möller and M. Eduard Gröller

Collaborative Brushing and Linking for Co-located Visual Analytics of Document Collections
Petra Isenberg and Danyel Fisher – In this paper they discuss a collaborative interface to interact with a collection of documents. The collaborative interface is called Cambiera and is a table top analytics tool. You can also see a video of users interacting with Cambiera on Youtube.

Here are some of the other papers that I thought were very interesting and hope to go through them in more detail (as they become available) :

Illuminated 3D Scatterplots
Harald Sanftmann, Daniel Weiskopf – In this paper, the authors tackled an important and challenging problem of visualizing 3D scatterplots. 2D scatterplots are well known to convey data effectively. The use of illumination to better visualize the 3D nature of the data was a very elegant solution and seems to work quite well.

Instant Volume Visualization using Maximum Intensity Difference Accumulation
Stefan Bruckner and M. Eduard Gröller – This paper proposes a novel way to integrate along the ray in the volume rendering process. The idea is very unique and provides excellent results. Since techniques such as MIP, DVR are part of every volume rendering course, seeing such novel and interesting techniques is always exciting.

Semi-Automatic Time-Series Transfer Functions via Temporal Clustering and Sequencing
Jonathan Woodring, Han-Wei Shen – Time-varying data visualization is always challenging due to the large amounts of data that needs to be visualized. The authors propose a clustering and sequencing based technique to generate ’semi-automatic’ transfer functions for the data.

A Directional Occlusion Shading Model for Interactive Direct Volume Rendering
Mathias Schott, Vincent Pegoraro, Charles Hansen, Kévin Boulanger, Kadi Bouatouch – I enjoyed reading this paper a lot since people rarely seem to talk about anything other than ambient occlusion these days. This paper presents an elegant and unique way to provide occlusion shading with reasonable frame rates. Looking forward to implementing this soon.

Visualization of Vessel Movements
Niels Willems, Huub van de Wetering, Jarke J. van Wijk – This paper provides a very beautiful solution to the problem of visualizing vessels coming in and out of a port. I enjoy reading J. J. van Wijk’s papers and this and the next one are not any different.

Force-Directed Edge Bundling for Graph Visualization
Danny Holten, Jarke J. van Wijk – The authors follow up on the excellent paper from IEEE Vis 2005 on ‘Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data‘ (which was mentioned in one of my previous posts on Seminal infovis papers), with another great paper. This paper has already received a lot of attention here, here and here. Here is a screenshot showing migration patters in the united states.

Context-Aware Volume Modeling of Skeletal Muscles
Zhicheng Yan, Wei Chen, Aidong Lu, David Ebert

Map Displays for the Analysis of Scalar Data on Cerebral Aneurysm Surfaces
Mathias Neugebauer, Rocco Gasteiger, Oliver Beuing, Volker Diehl, Martin Skalej, Bernhard Preim

Visual Analysis of Brain Activity from fMRI Data
Firdaus Janoos, Boonth Nouanesengsy, Raghu Machiraju, Han Wei Shen, Steffen Sammet, Michael Knopp, István Á. Mórocz

This post was heavily inspired by an article in the Economist magazine which can be found at http://www.economist.com/science/tq/displaystory.cfm?story_id=13725877

I wanted to draw the attention to some of the excellent information from the article and hope that we see many such endeavors. 

Maplight.org – Money and Politics: Illuminating the connection 

Dan Newman of MAPLight.org, a group based in Berkeley, California that charts the links between politicians and money.

With maps, you can show people how an abstract concept connects to where they live.

Starting in January 2007, it tracked which states (those growing sugar-beets and sugar-cane, it turned out) were making the most generous political donations in the run-up to a vote in July 2007 on subsidies for the sugar industry.

The Grim Reaper’s road map: An atlas of mortality in Britain
by Mary Shaw, Bethan Thomas, George Davey Smith and Daniel Dorling. More information, visualizations and even data can be found at 
http://www.sasi.group.shef.ac.uk/publications/reaper.html. Here’s a screenshot from their book. 

Kirwan Institute for the Study of Race and Ethnicity in Columbus, Ohio project- Masstrack.org. This visualization shows the geographical locations of the workforce in innovation sectors in Massachusetts. As can be expected, the concentration in the Boston and Cambridge area is very high as compared to the rest of the state. 

Social explorer lets you explore, save and create slidshows of visualizations of the census 2000 data. The first screenshot shows the interface that allows you to interact with the data. The bottom screenshot shows the median age around the New Haven, CT area. Since, New Haven is mostly a college town, the median age being lower than the surrounding counties in Connecticut makes sense.

Ushahidi, which means ”testimony” in Swahili, is a very innovative website that was developed to map user reported violence in Kenya after the post-election fallout at the beginning of 2008. It has already been adapted and used by votereport.in and swineflu.ushahidi.com.

The top two images show Violence and Voter inconsistencies as reported by users. The bottommost image shows Swine Flu cases all over the world. Such field reporting-based visualizations can be invaluable, especially now that a worldwide swine flu pandemic has been declared by the WHO. In a previous post, we have seen different visual representations of the Swine Flu Pandemic. 

My favorite quote from the article was “We don’t just want to be about mapping,” says John Kim of Healthy City. “Maps don’t change the world, but people who use maps do.” 

I would like to believe that today we can say something like “Visualizations dont change the world, but people who use visualizations do.” 

If you have seen other examples of visualizations that have impacted policies, laws or helped draw attention to a problem, please add it in the comments section.

Here is an article that I wrote at Vizworld.com. Vizworld.com is a great resource for all things related to graphics and visualization and is one of the websites that I regularly visit to keep updated with the field. This article has been updated with resources that some of the visitors mentioned in the comments section and I thank them for the same.

I have been thinking about making a list of some of the most seminal information visualization papers. These are papers that have made an impact and can be widely seen in the media (print/web) or are being adopted in visualization software/systems such as VTK, Prefuse, Many Eyes and so on. I may have missed out on a few papers, so please feel free to add any that you think are ‘must-reads’ for an infovis researcher.

Disclaimer: The list in no particular order of preference.

Here’s the list:

1. Cluster and Calendar based Visualization of Time Series Data, Jarke J. van Wijk and Edward R. van Selow, Proc InfoVis 99, p 4-9.
2. Polaris: A System for Query, Analysis and Visualization of Multi-dimensional Relational Databases, Chris Stolte, Diane Tang and Pat Hanrahan, IEEE Transactions on Visualization and Computer Graphics, Vol. 8, No. 1, January 2002.
3. The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations, Ben Shneiderman, Proc. 1996 IEEE Visual Languages. An interesting sentence from the paper – “Information exploration is inherently a process with many steps, so keeping the history of actions and allowing users to retrace their steps is important. However, most prototypes fail to deal with this requirement.” I feel that with the amazing ‘provenance’ based work that Claudio Silva’s group at the University of Utah are doing on Vistrails, some of this is being finally addressed.
4. How Not to Lie with Visualization, Bernice E. Rogowitz and Lloyd A. Treinish, Computers In Physics 10(3) May/June 1996, pp 268-273.
5. Excentric Labeling: Dynamic Neighborhood Labeling for Data Visualization. Jean-Daniel Fekete and Catherine Plaisant. Proc. CHI’99, pages 512-519. There is a new paper this year at EuroVis 2009 that extends the techniques proposed in this paper – Extended Excentric Labeling by Enrico Bertini, Maurizio Rigamonti and Denis Lalanne. 
6. VisDB: Database Exploration using Multidimensional Visualization, Daniel A. Keim and Hans-Peter Kriegel, IEEE CG&A, 1994
7. Parallel Coordinates: A Tool for Visualizing Multi-Dimensional Geometry. Alfred Inselberg and Bernard Dimsdale, IEEE Visualization ‘90, 1990.
8. Smooth and Efficient Zooming and Panning. Jack J. van Wijk and Wim A.A. Nuij, Proc. InfoVis 2003, p. 15-22
9. Snap-Together Visualization: Can Users Construct and Operate Coordinated Views? Chris North, B. Shneiderman. Intl. Journal of Human-Computer Studies, Academic Press, 53(5), pg. 715-739, (November 2000)
10. Hotmap: Looking at Geographic Attention Danyel Fisher, IEEE TVCG 13(6):1184-1191 (Proc. InfoVis 2007).
11. Tree visualization with treemaps: a 2-d space-filling approach, Ben Shneiderman, ACM Transactions on Graphics, vol. 11, 1 (Jan. 1992) 92-99 and B. Johnson and B. Shneiderman, “Tree-maps: A Space Filling Approach to the Visualization of Hierarchical Information Structures“, Proc. of Vis ‘91, Oct. 1991, pp. 284-291.
12. Danny Holten (2006), Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data, IEEE Transactions on Visualization and Computer Graphics, vol. 12, no 5, pp. 741-748. – This has already been implemented in VTK and is very useful for visualizing hierachical data.
13. Tamara Munzner, Francois Guimbretiere, Serdar Tasiran, Li Zhang, and Yunhong Zhou (2003), TreeJuxtaposer: Scalable Tree Comparison using Focus+Context with Guaranteed Visibility, SIGGRAPH 2003 , published as ACM Transactions on Graphics 22(3), pp. 453-462.
14. M. Stone, “Choosing Colors for Data Visualization“, 2006.
15. Penny Rheingans (1999). Task-based Color Scale Design. Proceedings of Applied Image and Pattern Recognition ‘99, SPIE, pp. 35-43.
16. F. Viegas, M. Wattenberg, F. van Ham, J. Kriss, and M. McKeon, “ManyEyes: A Site for Visualization at Internet Scale“, IEEE Trans. on Visualization and Computer Graphics, Vol. 13, No. 6, Nov.-Dec. 2007, pp. 1121-1128.
17. J. Heer, S. Card, J. Landay, “prefuse: a toolkit for interactive information visualization“, Proceedings of ACM CHI ‘05, April 2005, pp. 421-430.
18. John Lamping , Ramana Rao , Peter Pirolli, A focus+context technique based on hyperbolic geometry for visualizing large hierarchies, Proceedings of the SIGCHI conference on Human factors in computing systems, p.401-408, May 07-11, 1995, Denver, Colorado, United States
19. S. Havre, B. Hetzler, and L. Nowell, “ThemeRiver: Visualizing Theme Changes over Time”, Proceedings of the 2000 IEEE Information Visualization Symposium, Salt Lake City, Oct. 2000, pp. 115-123. Image from Theme river inspired work – Stacked Graphs: Geometry & Aesthetics, Lee Byron, Martin Wattenberg, IEEE InfoVis 2008
20. M. Wattenberg and J. Kriss, “Designing for Social Data Analysis,” IEEE Transactions on Visualization and Computer Graphics Vol. 12, No. 4, Jul.-Aug. 2006, pp. 549-557.

Other than these papers, these books are a source of invaluable advice about visualizing data.

Books

• Tufte, Edward R. (2001). The Visual Display of Quantitative Information (2nd ed.). Cheshire, CT: Graphics Press. ISBN 0961392142.
• Tufte, Edward R. (1990). Envisioning Information. Cheshire, CT: Graphics Press. ISBN 0961392118.
• Tufte, Edward R. (1997). Visual Explanations: Images and Quantities, Evidence and Narrative. Cheshire, CT: Graphics Press. ISBN 0961392126.
• Few, Stephen (2004). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press. ISBN 978-0970601995.
• Few, Stephen (2006). Information Dashboard Design: The Effective Visual Communication of Data. O’Reilly Media. ISBN 978-0596100162.
• Few, Stephen (2009). Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press. ISBN 978-0970601988.
• Ware, C. (2004) Information Visualization: Perception for Design. (2nd Edition) Morgan Kaufman. December, 435 pages.
• Ware, C. (2008) Visual Thinking for Design. Morgan Kaufman
• Casey Reas and Ben Fry (2007), Processing: A Programming Handbook for Visual Designers and Artists. MIT Press. 736 pages.
• Ben Fry (2007), Visualizing Data, O’Reilly. 384 pages.
• William S. Cleveland (1985). The Elements of Graphing Data, Hobart Press.
• William S. Cleveland (1993). Visualizing Data, Hobart Press.

What other papers/books would you add to this list?

In the past, I have discussed visualization tools and a few companies that make them. They are used by a wide variety of professionals such as the Business Intelligence community, Scientific Data explorers, Financial data analysts and many more users.

I feel though that more often than not such tools are an afterthought in a company’s think tank and require a significant amount of training, learning and overcoming a mental block by the senior management of a company. Companies such as Tableau Software, Spotfire, and many others must have excellent sales teams which, on identifying companies that may be able to benefit from their really stellar software, have to then pitch it to them. Even if the software blows the company management away, the reluctance on their part in adopting it surely must be a problem. Additionally, I am sure that even if the top management think its a great idea, the real users (lower level management/marketing/sales professionals) might not have the time and willingness to invest into using the software.

I know that the people behind these visualization companies are brilliant researchers who are not only innovating in the field of visualization but also taking the extra effort to improve on proven visualization techniques in order to make them easy to use. 

I feel very strongly about this matter and wonder if a few things can be done to avoid this situation in the future. Clearly, just as training radiologists and other medical software users to use 3D volume rendering software is an uphill task, training business analysts to use visualization tools must be a difficult task.

1 – Provide an educational version of the software that can be available and used only through academic institutions. They could be fully featured or have only some evaluation features but let your software be one of the first tools that students use when analyzing their data. That will ensure that at least a few of them will be trained in using the tool when they go on to join a company and root for your visualization software at the company. If you think about it, companies like Microsoft allow free downloads of their express edition of Visual Studio for students which ensures a familiarity with the software that developers then take to companies when they join there. In my experience, students are far more ready to learn new software and technologies as compared to senior management in a company. They also have more time on their hands and can devote more time to learn the spiffy new features in your visualization software.

2 – Developing a course or two for data analysis in conjunction with a professor at a university – Merely providing educational versions of the software is of limited value. An interesting data analysis course that teaches use of your software or two/three other similar software tools along with basics of data analysis and an overview of visualization techniques might be another interesting way to approach the problem.

3 – Provide easy to use learning material – Take the time and make sure to have tutorials and multitudes of examples on your website that will allow users to use them and improve over time. Having a free PDF book or a step-by-step tutorial can vastly benefit the user and take some load off of your hands for training purposes. Tableau software does an amazing job in the training realm as can be seen by the examples at http://www.tableausoftware.com/learning/examples. You can even download a ‘workbook’ for each example and play around with it in your copy of the software.

4 – Provide free training in the form of Webcasts – Recently, nvidia had a few webcasts focused on CUDA and its applicability for general purpose computing on the GPU. The webcast consisted of a few nvidia developers giving a presentation and answering some questions at the end. The webcast was free and was a great way to indoctrinate a few more researchers to use CUDA for which they would have to buy nvidia graphics cards. I thought it was a great idea which could be taken even further when applied to visualization software. If your users already have a running software, then publishing sample datasets and walking them through it can be even more compelling and interactive than reading an online tutorial or a book chapter.

5 – Providing training at a conference or a workshop might be another way to get users to download your evaluation version and play with some data. Google has been doing similar ‘training’ at conferences like SIGGRAPH and IEEE Visualization for the last couple of years now. This helps you get new users as well as allow for professionals attending the conference to learn something they might convey to their company when they go back to work, which could translate into acceptance and added sales for the company.

If you have any other suggestions, please feel free to let me know. Sorry there are no pretty visualizations in this post