Web Visualization @ NCSU

Find: WebGL Playground

2012-01-27T12:44:00.001-08:00

GameDev News

WebGL playground is a straightforward idea: type in your WebGL script and see the results. But the cool part is that the editor and the results are just on the same page and that you get a handful of features that make your life easier.

Sent with Reeder

Competition: Data Journalism Awards now accepting submissions

2012-01-22T22:20:00.001-08:00

A competition in news oriented visualization and apps.

Data Journalism Awards now accepting submissions

Google

Last November, we announced our support for a new Data Journalism competition, organized by the Global Editors Network. The competition is now open to submissions and today we hosted an event at our offices in London to share details on how to compete and win a total of six prizes worth EUR 45,000. The European Journalism Centre is running the contest and Google is sponsoring.

Journalism is going through an exciting—if sometimes wrenching—transition from off to online. Google is keen to help. We see exciting possibilities of leveraging data to produce award-winning journalism. “Data journalism is a new, exciting part of the media industry, with at present only a small number of practitioners,” said Peter Barron, Google’s Director of External Relations. “We hope to see the number grow.”

In data journalism, reporters leverage numerical data and databases to gather, organize and produce news. Bertrand Pecquerie, the Global Editor Network’s CEO, believes the use of data will, in particular, revolutionize investigative reporting. “We are convinced that there is a bright future for journalism,” he said at the London event. “This is not just about developing new hardware like tablets. It is above all about producing exciting new content.”

The European Journalism Centre, a non-profit based in Maastricht, has been running data training workshops for several years. It is producing the Data Journalism Awards website and administering the prize. “This new initiative should help convince editors around the world that data journalism is not a crazy idea, but a viable part of the industry,” says Wilfried Ruetten, Director of the center.

Projects should be submitted to http://www.datajournalismawards.org. The deadline is April 10, 2012. Entries should have been published or aired between April 11, 2011 and April 10, 2012. Media companies, non-profit organisations, freelancers and individuals are eligible.

Submissions are welcomed in three categories: data-driven investigative journalism, data-driven applications and data visualisation and storytelling. National and international projects will be judged separately from local and regional ones. “We wanted to encourage not only the New York Times’s of the world to participate, but media outlets of all sizes,” says Pecquerie. “Journalism students are also invited to enter, provided their work has been published.”

An all-star jury has been assembled of journalists from prestigious international media companies including the New York Times, the Guardian and Les Echos. Paul Steiger, the former editor-in-chief of the Wall Street Journal and founder of the Pulitzer Prize-winning ProPublica, will serve as president.

Winners will be announced at the Global News Network’s World Summit in Paris on May 31, 2011.

Posted by William Echikson, External Relations

Find: @seismologists collect #data, 140 characters at a time

2012-01-21T21:25:00.001-08:00

Twitter and phones collect quake data.

@seismologists collect #data, 140 characters at a time

Ars Technica

On August 23, 2011, a magnitude 5.8 earthquake centered 40 miles northwest of Richmond, Virginia had the East Coast abuzz. As you’d expect, social media lit up as people reported the experience. You can actually see the travel of the seismic waves if you map out the tweets containing the word "earthquake." While that’s no match for the beautiful data recorded by the EarthScope seismic network, some researchers see the beginnings of a data revolution.

Count Richard Allen, a seismologist at the University of California-Berkeley, among those who want to ride the wave. In a perspective article published in Science, he argues that crowdsourced earthquake data is a potential gold mine.

Find: WebKit in Your Living Room

2012-01-19T05:39:00.001-08:00

WebKit in Your Living Room

The Netflix Tech Blog

Hi, it's Matt Seeley, engineer on the device UI team at Netflix. My team uses WebKit, JavaScript, HTML5 and CSS3 to build user interfaces for the PlayStation 3, Wii, Blu-ray players, Internet-connected TVs, phones and tablets.

Recently I spoke at the HTML5 Dev Conf about WebKit-based UI development on consumer electronics. I discussed:

Responding to user input quickly while deferring expensive user interface updates
Managing main and video memory footprint of a single page application
Understanding WebKit's interpretation and response to changes in HTML and CSS
Achieving highest possible animation frame rates using accelerated compositing

Watch the video presentation from the conference:

Slides are also available in PDF

Astute readers will realize that portions of the content are also suitable for mobile and desktop development. It's all about building great user interfaces that take best possible advantage of the device.

Interested in joining our team? We're hiring!

Sent with Reeder

Data: Vehicles involved in fatal crashes

2012-01-18T18:15:00.001-08:00

Vehicles involved in fatal crashes

FlowingData

After seeing this map on The Guardian, I was curious about what other data was available from the National Highway Traffic Safety Administration. It turns out there's a lot and it's relatively easy to access via FTP. What's most surprising is that it's detailed and fairly complete, with columns for weather, number of people involved, date and time of accidents, and a lot more.
The above shows vehicles involved in fatal crashes in 2010 (which is different from number of crashes or number of fatalities). This data was just released last month, at the end of 2011 oddly enough. It's a calendar view with months stacked on top of one another and darker days indicate more vehicles involved.
Nearly every single data point also has location attached to it, so I tried some mapping, but they look like population density more or less. Here's one that shows crashes that occurred on local roads (orange) and those on freeways, highways, etc (blue). Road patterns start to come out for the major interstates.

I also mapped by weather (rain, fog, snow), time of day (midnight to 4am, 4-8, 8-noon, noon to 4, 4 to 8, and 8 to midnight), and crashes due to drunk driving but it wasn't as interesting as the day-by-day.
If you're a teacher looking for data to use with an assignment or just want to practice, this is a good set, despite the somber topic. You can find the data here, and there's an FTP link in the footer of the page to download more detailed data. You'll also need this guide [pdf] that defines all the variables.

Viz: Amazon recommendation network

2012-01-18T18:09:00.003-08:00

Amazon recommendation network

FlowingData

Whenever you look at an item on Amazon, the site recommends related items that you might be interested in. So in a way, these items are connected by how people buy. Artist and designer Christopher Warnow uses the metaphor to create a network of Amazon products, where each node represents an item, and connections, or edges, represent common bonds of recommendations. Simply enter an Amazon link, and Warnow's software generates a network.

For example, the image above is the network for Edward Tufte's Visual Display of Quantitative Information, although Stephen Few's Information Dashboard Design seems to have more connections for some reason. My quick guess is that book's that are less niche have more connections, because when I entered Visualize This, the network was pretty small. Although I would've thought that Tufte's book would have a larger network than Few's.

In any case, the application and Processing code is free to play with. Warnow uses Gephi for network connections and grouping. Or if you don't feel like downloading a 60mb file, you can just watch it in action in the video below.

You might also be interested in Yasiv. It's a web app with a similar idea, but not quite as slick of an implementation.

[Christopher Warnow via Datavisualization]

Sent with Reeder

Viz: Spot visualizes tweet commonalities

2012-01-18T18:09:00.001-08:00

Not a lot new here.

Spot visualizes tweet commonalities

FlowingData

Twitter is an organic online location, full of retweets, conversations, and link sharing. Jeff Clark tries to show these inner workings with his newest interactive, Spot. Enter a query in the field on the bottom left, and Spot retrieves the most recent 200 tweets. You then can choose among five views: group, words, timeline, users, and source.

Each tweet is represented by the tweeter's profile picture, and they rearrange themselves as you switch between views. The latter three views, timeline, users, and source, arrange tweets into bar charts. Fairly straightforward.

Spot gets interesting with the first two views though, groups and words. Tweets are arranged based on the words they use.

Above, for example, is the word view on the search "flowingdata." Tweets cluster around words like world and data. Below is the same search, but with the groups view. Users who tweeted similar text (usually retweets) are grouped together. What jumped out at me was the group on the bottom with a single user's face. That turned out to be a spammer.

Give it a try for yourself here.

Find: Color filtering Van Gogh

2012-01-13T18:33:00.001-08:00

Via former lab member Alex Kuhl. Interesting color deficiency study applied to van gogh.

Best, Ben

---------- Forwarded message ----------

Posted this to my Twitter feed, but thought I'd send this along to you guys in case you don't catch it on there.

http://asada0.tumblr.com/post/11517603099/the-day-i-saw-van-goghs-genius-in-a-new-light

Viz: Politico analyzing Facebook user data to measure political sentiment

2012-01-13T05:55:00.001-08:00

Even private posts.

Politico analyzing Facebook user data to measure political sentiment

The Verge - All Posts

Facebook just made another move that might upset those concerned with the privacy of their data. The social media giant has started providing politics publication Politico with information on users sentiment towards the Republican presidential candidates as we approach the January 21st South Carolina primary. Politico exclusively receives mentions of the political candidates through posts and comments on Facebook — including material that users have marked as private, according to All Things D. However, Facebook claims it uses automated tools to send information to Politico without any personally identifying information and that no Facebook employees actually read the posts. In addition to Facebook-mined data, the company will also be...

Tool: Plot.io

2012-01-12T17:53:00.001-08:00

From Robert Kosara

Plot.io

Data visualization startup Plot.io has been making some noise lately. From what I know so far, it looks a lot like Tableau, but presumably works in the browser. This could be a potential successor to Swivel, which folded a bit over a year ago, and maybe what Verifiable was trying to do.

Their teaser video is a bit confusing, but what it shows is an interface that looks a lot like Tableau. On their Twitter feed, they also talk about marks, and they seem to be aware of what is going on in the visualization community. They’re certainly worth watching.

Find: My Review of Visualize This and Visual Complexity for Science Magazine

2012-01-12T17:47:00.001-08:00

Viz this sounds interesting.

My Review of Visualize This and Visual Complexity for Science Magazine

I was asked to write a review of two recent visualization books for Science: Nathan Yau’s Visualize This and Manuel Lima’s Visual Complexity. The piece appeared in the last issue of 2011, right before Christmas. Below is a link to the review and some additional comments on it and the two books.

Discussing the two books in one review was quite a challenge, because they are so different. Visualize This is very hands-on and walks the reader through a number of examples, while Visual Complexity is an illustrated guide with a heavy theoretical bent.

Visual Complexity

I’m really conflicted about Visual Complexity. While it is a beautiful book that provides a great overview over a large range of visualization examples, it has one big flaw: it doesn’t deliver on the promise of structuring and understanding network visualization techniques.

That’s disappointing for two reasons: a very prominent quote on the back compares Lima to Edward Tufte, and the book’s structure suggests a deeper and clearer understanding of how network visualization works. As I point out in my review, I think the Tufte remark misses the point and actually does more harm than good by raising expectations too high. But as Stephen Few also mentions in his review, expectations of Lima are also higher because of his excellent Information Visualization Manifesto. While there is a lot of historical context to be found in the book (almost too much, in fact), and there are some really good insights, it just feels incomplete. It’s as if the book was published before he could finish it.

One issue that is only mentioned in a footnote in the review (and that I had originally intended to leave out completely) are the additional essays by Nathan Yau, Andrew Vande Moere, and others in the final chapter of Visual Complexity. They seem mostly disconnected from the book, and in any case don’t appear to contribute anything of substance to the topic of network visualization. The space could have been much better used to expand on some of the interesting discussions in Lima’s own final chapter, or the structure of his “new language.” As it is, the book only teases what that might be by showing examples, but doesn’t go into enough depth on what the structure of that language might be, or how Lima picked his categories.

All that said, it’s still a wonderful resource with a huge number of examples and a good first step into figuring out the str...

Viz: Embracing Uncertainty in Two-Line Charts

2012-01-12T06:57:00.001-08:00

I like Robert's alternative. As he says, we need to show the undecided.

Embracing Uncertainty in Two-Line Charts

As we’re heading towards elections again, there is a chart type that is as unavoidable as political ads, baby-kissing, and smear campaigns: line charts showing polling data. The most common pitch two candidates against each other, and often make a big deal out of the fact that the lines cross. Not only are these charts misleading in the way they depict the choice, they also hide an important fact: the number of undecided voters.

The following image shows slightly different data, but the idea is the same. The data is from a long-running Gallup poll about job approval ratings of President Obama, from early 2009 to the end of 2011. Each data point is actually a three-day average. Blue shows approval, green disapproval.

There is a clear trend here that shows approval dropping from very high in early 2009 to just below 50% in mid-2010. From there, things get murkier. The blue and green lines cross, then continue for a while, then cross again. There’s clearly a lot of noise, but every inversion looks like a big event.

The thing that also stands out is the symmetry: since there are (apparently) only two choices, the disapproval percentage is always going to be 100% minus the approval percentage. That is visually very appealing, but it also creates the illusion of two independent values, shown as different lines, being in much more agreement than would be expected. There is also a lot of noise in the regions where the lines cross or are close to crossing, which make it hard to see what is going on.

An Alternative

How else could the data be shown? In particular, what else is there to show about this data? There are two aspects to the data that are getting lost in the line chart above: the number of undecided people, and the fact that the numbers have to add up to 100%. It also makes sense to reduce the noise and make it easier to see the trend, especially in parts where the approval and disapproval numbers are very close together.

Here is my alternative. It is a stacked area chart that contains the approval at the bottom, the undecided percentage in the middle, and the disapproval on top. The colors were chosen deliberately to be easy to interpret (red is bad, blue is like above and it’s also the color of the Democratic Party), and the undecided layer is actually transparent.

How is this better? For one, it shows the approval trend in a much clearer way than the first chart. If we assume that the number of undecideds is constant, we don’t actually need to see the disapproval numbers, and so can initially ignore anything above the blue area.

But the undecided perc...

Find: Teaching with Mobile

2012-01-10T20:03:00.001-08:00

In class quizzing using phones. Good idea!

Teaching with Mobile

Ever wish you could get your students to stop texting and start using their phones productively in the classroom? Do you ever wish for an easy and quick way to measure what your students have learned? If so, you’ll be excited to learn that we recently open-sourced our internal Quiz & Poll App for Android. Developed by our internal learning systems team, “Quiz & Poll” enables educators to engage and challenge their students inside the classroom (using polls) and outside the classroom (using quizzes).

How it works

With Quiz & Poll, teachers & educators can create quizzes and polls easily using Google Spreadsheets. Quizzes and Polls are distributed to students via the Android app or an embeddable webplayer. Statistics data is written back to the spreadsheet so the instructor can track student responses and understanding.

Key Features

Quizzes and polls are easily created and administered on Google Spreadsheets.

Students can download the Android App to take the quiz or live classroom poll.

For students without Android phones, quizzes and polls can be accessed via a web interface (works on laptops, iPhones, iPads etc.).

Administrators can view quiz and poll statistics on the same Spreadsheet.

The quizzing app and leaderboard

How it’s built

The Quiz & Poll application showcases how you can combine several Google technologies to make an easy to use app. The code is useful for developers curious about following technologies and how they interact:

Android app communicating with backend on AppEngine (Python+Django)

AppEngine backend is communicating with GData Spreadsheets API

Google Apps Script (used for interface to administer polls)

Closure Javascript framework ...

Tool: How the world was open sourced

2012-01-10T19:57:00.001-08:00

Google doodle source code.

How the world was open sourced

Once in awhile at Google our illustrators get excited about lasers, Morse code, H. G. Wells’s The War of the Worlds – and then come up with beautiful Google doodles that find their way onto our homepage. Sometimes our programmers also get excited and team up with the illustrators, and that’s how we found ourselves with Google doodles celebrating Les Paul’s guitar, Pac-Man, Jules Verne’s bathyscaphe, and even your own customized turkey that you could then share on Google+.
I’m one of those people who is more comfortable with 80 monospaced characters endlessly repeated than with a paintbrush. Earlier this year I worked with Sophia Foster-Dimino from the Google doodle team on a doodle celebrating Stanisław Lem, my favorite sci-fi writer and philosopher.

pmr
Just like picking the right paintbrush and palette is important for all our doodles, so is figuring out the right technologies and proper user interface for those we want to make interactive. That’s something I’m personally really excited about and that’s why today I wanted to share that excitement and the entire source code of the Stanisław Lem doodle with you – accompanied with an article explaining HTML5 technologies that we used… or didn’t use:

read the article about Stanisław Lem doodle on HTML5 Rocks

view the complete source code

Apache 2.0 License

Creative Commons BY-NC-SA 3.0 License

Data: New in the Campaign Finance API: Independent Expenditures

2012-01-07T12:50:00.001-08:00

New in the Campaign Finance API: Independent Expenditures

The Campaign Finance API now supports independent expenditure data.

Data: Two New Client Libraries: Times Wire and Campaign Cash

2012-01-07T12:48:00.001-08:00

Two New Client Libraries: Times Wire and Campaign Cash

Announcing two new Ruby clients for New York Times APIs: Times Wire and Campaign Cash.

Viz: bitly in 2011

2012-01-07T12:22:00.001-08:00

Links we clicked on in 2011. 3% of all uvem were about celebs. Actually, seems low to me.

bitly in 2011

From Kim’s short-lived marriage to the earthquake up and down the east coast of the US, more data resonated through the social web this year than ever before.

actual real human clicks on bitly links (by day) in 2011

World events reshaped the geography of the Internet, such that we saw 392 times the number of clicks on Egyptian (.eg) URLs in 2011 than in 2010.

The number of new social sharing platforms continued to increase with the addition of new networks like Google Plus and chime.in.

Even diddy and the Dalai Lama got their own bitly short domains this year:

and

And boy does the social web love celebrities!

all of the clicks in 2011

Yes, 3% of all clicks on links went to pages about top celebrities this year, including some of our favorite gaffes and rumors:

But don’t lose faith in humanity! We saw significant traffic to the top news stories around the year’s meaningful events:

Jan 2011: Obama’s Speech, The New Yorker

Feb 2011: Photos from the Protests in Egypt, The New York Times

Mar 2011: Massive Earthquake Hits Japan, boston.com

Apr 2011:

Find: Animate webpage elements with Scrollorama jQuery plugin

2012-01-05T18:43:00.001-08:00

Animate webpage elements with Scrollorama jQuery plugin

Web development has surely evolved over the years — Flash has fallen out of flavor and been replaced by techniques that take advantage of native web browser capabilities using tools like CSS and jQuery. That progression has paved the way for the creation of some pretty neat things, including a new tool from web developer John Polacek called Scrollorama. This jQuery plugin will take just about any HTML element (pictures, video, text) within a webpage and animate it in conjunction with scrolling. Animations include fading in, flying in, rotating and zooming, to name a few. If you'd like to tinker with a demo to see what we mean, hit the source link below and simply scroll down. And if you're a developer, feel free to download the plugin...

Project: Express Yourself

2011-12-16T06:52:00.000-08:00

About the project:

Every person has an opinion. With the wide and vastly used social networks these days, people like to express their opinion and know others opinions on various topics. A close observation of the patterns of people's opinions, how they change over time or how consistent they are gives us a better understanding of what people perceive and what they want- may be in the field of politics, may be at a work environment or in just a friends circle. This is facilitated by our app, Express Yourself, which presents a real-time visualization of user opinions.

Express Yourself , as the name suggests allows users to express themselves by allowing them to create their own polls and cast a vote to polls by others. The app presents a visualization of the poll results of every poll, against a time series and the visualization is updated every 10 seconds to capture change in users' opinions. These polls may be about what users think of the current government or just a simple question on previous day's basketball match!

The user needs to login via Facebook and is all set to go! He can create polls, respond to polls, view the visualizations. The user clicks on any of the questions to view the real-time visualization of responses. The visualization is in the form of a line graph against a time series. Color legends and background labels make the visualization self-explanatory. The vote he casts can be a range between 1-7 expressing his percent support to that option. The user has his own profile page that displays the posts he created, his responses and the percentage of support to his vote. The home page of the app displays the popular posts and the new polls. The user is also provided a "Search" feature letting him to look through the archives. Also, when he creates a new post, the app pulls up similar questions, so that he does not create them again.

Links:

Live app deployed on Amazon EC2: http://50.16.148.163:3000/
Video demo of the app: http://www.screenr.com/YIvs
Source code: https://github.com/pique/ExYou.git

Development:
We have built the website in Ruby on Rails framework. The visualization has been developed using the Highcharts.js JavaScript library and JQuery UI elements.

Further scope:
We aim to include newer features to improve the user input. We plan to include sparklines against the list of polls, create weekly, monthly, yearly tabs to display the visualization over a period of time. Our greater aim is to allow companies use this app to know about their employee moods, thoughts and needs. We believe this will be of great help and a source of constant employee feedback to the company.

We would like to thank Dr.Watson for his valuable feedback and constant support and guidelines throughout this project. We feel it has been a great learning opportunity. We also would like to thank all the guests for their feedback.

Team: Pradeep Kumar Ramaswamy (pramasw3), Gopikannan Venugopalsamy(gvenugo),
Shishir Kakaraddi(smkakara),Sridevi Venugopal(sthirum), Preeti Muppalla(ppreeti)

Project: Census of India

2011-12-15T15:39:00.000-08:00

Overview:

Census of India attempts to visualize the Indian population census of 2011. The population of India as of Feb 2011 is 1.2 billion which is a very large number and hence the census data is also large. In our project we have presented this data to the user in a good interactive way rather than plain textual form. The web visualization is interactive which map of India and charts to represent the data. In these charts we have presented some important categories such as the population size, sex ratio and literacy. We have also given a feature to compare 5 states so as to quickly know the trends of each state and who wins in which category.

Development:

We developed the site using HTML, CSS and JavaScript.

We made use of the HighCharts API for charts and ammap for the map.

Editor used was Microsoft Expression Web 4.

Data set was the XML file containing data. This file is available for download on the website itself.

Website hosted on:

http://www4.ncsu.edu/~aasahasr/CensusIndia2011/

Source Code:

https://github.com/NCSUWebViz/Indian-Census

Screen cast on YouTube:

http://www.youtube.com/watch?v=xeFg_cNDGx0

Team:

Aditya Sahasrabuddhe, Anuj Sharma and Pavan Gopal Bandla

We would like to thank Dr. Watson for his help and invaluable feedback throughout the studio sessions which helped us in iterative designing of the visualization. We would also like to thank all the guests ( present during studio sessions and the final presentation) for their important feedback.

Project: Baseball Visualization

2011-12-15T14:50:00.000-08:00

Baseball Visualization attempts to capture important statistics in the history of baseball over the past 100 years in the form of data sets and the visualization is done on the data by using HTML, CSS, Javascript and JQuery. Using this visualization tool, we have uncovered some important correlations in the history baseball by analyzing the players performance, U.S. statewide statistics and the performance of the teams in the American and National leagues. We have also shown how significant events in the history of baseball have had an impact on the game and on the different leagues. It is easy to navigate the homepage and find the visualization tools that we have built. We have also embedded a link for GitHub for ease of navigation to the source code from the homepage. Please feel free to express your comments that will help us in the future development of the project.

Here are the links:

Source code - https://github.com/NCSUWebViz/Baseball - https://github.com/charanlekkalapudi/Baseball-Visualization

Visualization site - http://www4.ncsu.edu/~vkpatnan/latest-all/

Data set - http://www.baseball-databank.org/files/BDB-sql-2011-03-28.sql.zip

Screencast - http://www.youtube.com/watch?v=Okd9srskgdI

Who are we ?

Vikhyath Reddy Marapadaga (vmarapa), Charan Chaudary Lekkalapudi (clekkal), Vinay K. Patnana (vkpatnan) & Ravi Teja Manda (vrmanda).

We express our sincere thanks to Dr. Watson for guiding us in the project and providing us valuable feedback that helped us stay on proper course in the project.

Reaction: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods

2011-12-15T12:27:00.003-08:00

Dealing with the subjectivity of visualization, the authors identified the need for a scientific foundation and they took some steps in that direction. The paper includes both theory and experimentation that backs up the theory.

The first part of the theory is an identification of a set of elementary perceptual tasks. A second part is the ordering of the tasks. Experimentation consists on subjects recording their judgements of the quantitive information of the graph.

The theory and experiments support the conclusion: a complete change is need in the current graphs being used. The authors also purpose alternative graphs: dot charts, dot charts with grouping and framed-rectangle charts. Even when I understand the problems presented in this graph, I don’t really find the new graphs better or being used in the long-term (which apparently happened).

Reaction: Imaging Vector Fields Using Line Integral Convolution

2011-12-15T12:27:00.001-08:00

The authors present a new method for imaging vector fields using line integral convolution (LIC). A comparison is made between DDA convolution and Line Integral Convolution. The flaw in DDA convolution is that it renders vector fields unevenly, small scaled surfaces loss detail. LIC is an alternative presented on this paper that doesn’t have this flaw, because it uses a different approach for approximating vectors.

The paper is a little complicated and the authors go through all the technique. He discusses its application, implementation, and advantages. Its advantages include: removing the aliasing error, its flexibility (ability to interface with other techniques).

Reaction: Marching Cubes: A High Resolution 3D Surface Construction Algorithm A new algorithm (at the time) for drawing isosurfaces (analog to isolines

2011-12-15T12:26:00.002-08:00

A new algorithm (at the time) for drawing isosurfaces (analog to isolines) was presented in this paper: Marching Cubes. The basic idea is to break the volume into smaller volumes (divide and conquer). Then each cube is classified into 15 configurations (256 reduce into 14 patterns after two different symmetries). According to external sources I read, the original algorithm contains mistakes and additional cases where added.

The name comes from the concept that after calculating a cube, we march (move on) to the next cube. The algorithm was implemented in C and demoed using medical 3D images. The results are impressive, and more if we consider the year.

At the end of the paper, the authors comment of a new algorithm, diving cubes. It draws points instead of triangles, it works because as the resolution increases the number of triangles approaches the number of pixels displayed.

Reaction: Task Taxonomy for Graph Visualization

2011-12-15T12:26:00.001-08:00

Until now I thought that making visualizations was an artistic task. Not entirely true, but I never saw or thought about the procedure as a fixed list of tasks. The artistic component and subjective appreciation of visualizations make it hard to measure and evaluate. The authors provide a taxonomy, benchmark datasets, and specific tasks that would help both designers and evaluators.

The idea is to break this tasks into lower level tasks, and for this the authors add two general tasks to those purposed by Amal et al. Tasks are grouped in four groups: topology-based, attribute-based, browsing and overview tasks.

General descriptions and examples are given for each task.

Reaction: CH. 11: INFORMATION VISUALIZATION FOR TEXT ANALYSIS

2011-12-15T12:25:00.005-08:00

Text analysis is a field that I didn’t thought about it before this class. For me its interesting too discover new information on data already available to us: text mining Twitter posts and Facebook comments could give an impressive amount of information to researches and businesses equally.

This chapter provides a snapshot of visualization tools applied to text: visualizing text mining results, document concordance and word frequencies, and literature and citation relationships. For text mining many tools are shown including the JIGSAW. Word concurrence visualizations are by far, my favorites: the DocuBurst it’s impressive, TextArc looks very useful, but very hard to display, due to it’s size; of course, zooming controls. Tag clouds are always fun, and the “Word Nebula” project done by my fellow classmates seems a right step forward.

Finally, the chapter shows visualization tools for relations in literature. One example, is a graph showing relationships among scientific disciplines. Just thinking about a table showing the same data, makes me see the importance of visualization in this and other cases.

Reaction: Jigsaw: Supporting Investigative Analysis through Interactive Visualization

2011-12-15T12:25:00.004-08:00

Jigsaw is a visualization tool that helps investigative analysts that work with collections of text document. It visualizes the documents and the entities (place, person, things) on them. The input are reports written in natural language and of a length of about 1-5 paragraphs. Output is done in four different views: List View, Graph View, Scatterplot View, and Text View.

The List View shows lists of types of entities, side by side, connected by a line if they appear on a same report. Graph View shows a graph with reports and entities and lines in between. Scatterplot View shows types of entities in the X and Y axis (I did’t understand the different colors show on the picture. Finally the Text View is the original text from the reports with the entities highlighted and color-coded according to its type.

The tool seems to be a good idea for dealing with this type of information, but I’ll be worried about how it performs with large amounts of information. The Graph View looks very nice with three reports, but a 100 could be tough to represent clearly. Other views will have problems too, for example: the tabs on the Text View will overflow, the Scatterplot matrix will be to big to be displayed or too cluttered, etc.

Project: Gmail Viz

2011-12-15T12:25:00.002-08:00

GmailViz is the project aimed at providing way to analyze your inbox using paramters like

last reply to a mail
importance based on frequency of mail
user importance in your inbox
average response rate
user importance
timeline of the mail -how frequently you reply and how often you receive the mails from certain senders.

We have used Java Servlets to talk to our database which is in built in oracle. We query the database generate the result and pass it as json viz ajax calls to javascript.

We analyze your inbox such that we find importance of each mail and present to you in graphical form. We also carry out other useful analysis like email overload- suggesting you the mails that ought to be deleted from your inbox because they have not been either replied to in a very long time or their importance in very close. We visualize such emails in form of a scatter chart and present you with the link to those mails such that you can go ahead and delete such mails thereby releasing free space in your mailbox.

We run a batch process to populate tables in our database. Once this batch process is completed by clicking on analyze button on home page which looks like figure shown below you can start analyzing your inbox -

index page for GmailViz

The following are some other screenshots from the vizualization that we do based on analysis of your inbox -

Chart showing timeline vs importance

Drill down from previous chart zoom-in on particular time period and giving granular details about importance

Email Overload with mail preview

Graph showing when was the user last replied

Graph showing keyword analysis

User importance in your inbox

We used Raphael js and Google Chart API for plotting the chart. The pages were developed using HTML5, CSS3 and Javascript.

Details:

Screencast: http://youtu.be/OdezjHWRM70
SourceCode: https://github.com/NCSUWebViz/Gmail
Site: http://csc591-gmailviz.csc.ncsu.edu:8080/GmailViz/
Data: We build our own dataset by the analyzing mail from your inbox

Team: Sarvesh Pai, Girish Pandit, Nidhi Pathak, Vartika Singh

Thanks to Prof. Dr Watson who provided us vital feedback at various stage of our project.
Also special thanks to Clayton Coleman, Bill Houghteling, and Prof. Patrick Fitzgerald for their valuable insight into our project during demo.

Reaction: Effectively Communicating Numbers

2011-12-15T12:25:00.001-08:00

This white paper discusses the best practices to present quantitative information from a BI perspective. The author explains the best means to graph quantitative data and to communicate a message effectively. The message is restated through the whole paper: a plot or chart can either communicate a message or not.

The author not only describes the advantages and disadvantages of points, lines, boxes and bars plots, but also details the key points to format and size axis to again, communicate a message effectively.

The article is full of recommendations and good practices, and as an added value it also briefly discusses quantitative analysis techniques like regression and how to communicate numbers effectively

Reaction: The Eyes Have It

2011-12-15T12:24:00.001-08:00

This paper does a good job explaining why visualization is both an art and a science. While it is true that it relies on basic principles and a structured approach, each visualization plot has inherent peculiarities and a particular design.

It describes the basic tasks as a checklist that should be carried out to design visualizations (overview, zoom, filter, details, relate, history, extract) and specifies correct techniques for particular analysis on various dimensions. It also relates it to why human perception responds differently to the particular stimuli from these techniques.

Since some of the above tasks and requirements are done intuitively to a certain extent, probably the most valuable discussion on the article is on querying and filtering. It briefly discusses the importance and usefulness on Boolean logic, Venn diagrams and decision tables as an optional filter before the exploratory plotting.

Reaction: Value of Information Visualization

2011-12-15T12:23:00.002-08:00

Information visualization is tangibly valuable. However it is very difficult to quantify this value, which is exactly where InfoVis comes as a valuable asset. The paper discusses a big number of topics that are relevant not only for visualization purposes, but also for data mining and unsupervised machine learning.

One of the biggest challenges of data mining is to explain patterns and associations in higher dimensions. While visualization can support and supervise the data mining algorithms in few dimensions, visualization is limited to explain only a few dimensions at a time.

There is also a detailed discussion on some classical examples for visualization like Napoleon’s march to Moscow and Snow’s cholera pandemic source illustration, two graphs we saw in class. The paper also does a very good job explaining basic principles and dimensions for InfoVis (proximity, similarity, continuity, symmetry, closure, relative size) and why they are all important. It includes relevant examples and illustrations that are to be used for further reference. However it lacks consistency when trying to quantify the value of InfoVis.

Reaction: Balancing Systematic and Flexible Exploration of Social Networks

2011-12-15T12:23:00.001-08:00

In this article the authors present SocialAction, which seems a fairly customizable way to visualize, analyze and interact with networks and their components. Recently, Social Network Analysis (SNA) has trended for its applicability to the fraud detection (through outliers and their links) and to estimate potential of a given population based on the behavior of some network elements. I believe that SocialAction is flexible enough to perform industry standard network analysis across analysis from these and other different industries.

SocialAction flexibility is outstanding. Its features include ordering, ranking, coloring, querying, and node rearranging. Nodes and links can be added, deleted, or selected upon customizable parameters. The exploratory analysis is well complemented through a friendly way to create standard plots. As expected, it is more difficult to analyze networks as the dimensions increase, particularly if links overlap. The tool also includes a way to analyze based on dimension reduction and network reduction.

Should the authors provide a case study for trending Social Network Analysis problems, like fraud detection and profit network potential, SocialAction would increase its chances of being the next ultimate tool for this kind of analysis.

Reaction: TileBars: Visualization of Term Distribution Information in Full Text Information Access

2011-12-15T12:22:00.001-08:00

Through these article the author exemplifies a tool he designed to simultaneously visualize a term as it appears through the length of the document, its frequency and its distribution across different documents. The user is given a lot of freedom, he has both the ability to specify the number of terms to analyze and which boolean connectors to use.

Today PDF and (Microsoft) Word documents query a term based on order of appearance. Search engines calculate relevance based on historic data and analysis algorithms. It would be interesting to contrast and compare the TileBars visualization tool with text documents as well as with search engines. This way the user could take advantage of a customizable, simultaneous way to visualize a given term and prioritize the output depending on a more robust criteria.

TileBars seem a useful tool, even for visualization only. However texttile algorithm does not seem very robust to explore document structure.

Reaction: Imaging Vector Fields Using Line Integral Convolution

2011-12-15T12:01:00.000-08:00

This paper talks about bluring textures along a vector field. The comparisons made in this paper are good.The paperdescribes a technique called the LIC.While describing
the LIC the author has discussed different things.LIC has several advantages that has been discussed.Some of the example images given are very interesting.

However the effect of understanding of vector fields was not very apparent by this paper to me initially.

Project: MoViz

2011-12-15T11:55:00.000-08:00

MoViz is a novel visualization that provides a single platform for all your movie rating and review needs. MoViz brings together rating and reviews from Rotten tomatoes, Amazon and IMDB to depict differences and similarities in ratings to help you decide better. If also shows you the number of users who trust a certain source.

This visualization does give a lot of importance to the consolidated ratings obtained from different sources. We have loaded the top 50 movies (from IMDN top 250 list) into our data store. The following is a snapshot of the Ratings tab:

The following are the details of the project:

The site: http://movievisual.appspot.com/

The team: Anil Kulkarni, Deepa Bantwal Baliga, Shilpa Srinivasan, Sreeja Ravikumar.

The source code: git@github.com:NCSUWebViz/Movies.git

The screen cast demo can be found here:

Project: Medipa

2011-12-15T11:27:00.000-08:00

Team: Juhee Bae, David Gao, Eric Helms, Justin Sherrill

Description: Getting access to medical images is a bit troublesome with the tools we have today. Medipa aims to resolve this by providing the necessary tool for medical professionals to upload medical images such as CT or MRI scan to the internet. This opens the door for patients to see his/her own scans as well as allow other medical professionals to collaborate. Medipa also provides additional tools for users to interact w/ the rendered model.

Site: http://ec2-50-17-138-152.compute-1.amazonaws.com/image/

Screencast: http://www.youtube.com/watch?feature=player_embedded&v=iw-of2ApyGM

Code: https://github.com/ehelms/medipa_web

Data: Uploaded to EC2 instance for viewing.

Note: The site itself have upload disabled due to not wanting to bog down the user experience interacting with images.

Project: A Better Tag Cloud

2011-12-15T07:01:00.000-08:00

The Project Description

Word and Tag clouds have been around for a while, but they are often criticized for not offering enough information or enough valuable information. Our team has attempted to improve on a basic tag cloud by offering additional data gathering, text manipulation, and word associativity analysis features, while still keeping the tag cloud fun.

This screenshot, shows the site in action with text scrapped from the vizclass.csc.ncsu.edu blog, with the word "data" clicked on:

The Details

The site: http://pamo.github.com/wordnebula/

The team: Pamela Ocampa, Juliane Foster, Michael Rountree, Andrea Villanes

The source code: https://github.com/pamo/pamo.github.com

The screencast: http://www.csc2.ncsu.edu/591projects/wordnebula/screencast.sw

The data: Can be gathered from blogs, twitter, or directly copy and pasted into the site

Project: Demystifying Cricket

2011-12-14T21:46:00.000-08:00

About the Project
Demystifying Cricket is an visualization which helps users to visualize and thus analyze statistical data related to the game of Cricket. Cricket is a popular sport in the Asian and European countries with a fan-base in millions. Cricket is a game which originated in England in 1877 and thus has a huge statistical data related to around thousands of matches played worldwide! However, there has been no attempt at making this data analyzable using the modern tools of visualization. We have done just that.

Our aim is to take this huge data-set of matches, series and players together and construct visualizations which will help an avid fan to play around and simplify the gleaning of information at the same time.

For the data-set, we have taken data from the site HowStat! which has a collection of data since 1877. The data on this site is humongous in every-way with no structure of a database available. Thus, we have created our own database using the data from this site.

The data-set or the database is in MySQL and can be found in the Github repository under the file-name 'Cricket.sql'.

For more information and description of our project, we have provided a detailed screen-cast and hosted them on YouTube.
Here are their links: Part 1 and Part 2.

Screen-shots of our application

Fig 1. The HomePage - World Cup Globe

Fig 2. The Cartogram Globe

Fig 3. Team Performance Chart

Fig 4. Head to Head Performance Chart

Fig 5. Batting Statistics Charts

The future work of our visualization focuses on making the database incorporate batting statistics for Test Matches and Bowling Statistics - thus to create a full-scale Cricket visualization Powerhouse. Furthermore, most of these charts can be modeled along the lines of a slider cum timeline which users can use to detect a significant pattern in their team's performance. We have so much data that we can also predict the probability of a team winning a game against one particular team at a particular venue!

Finally, here are the related links for our Project:

The Live Application: http://cricket.phpfogapp.com/
The Source Code: https://github.com/NCSUWebViz/Cricket
The ScreenCast(s): Part 1 & Part 2
The Team: Mayur Awaghade, Ameya Gholkar, Micheal Matthews, Swathi Subramanian

Thanks to Dr.Watson for an excellent course with great insight into visualizations and its concepts and also for guiding us throughout the course of the Project. We would also like to thank Clayton Coleman, Bill Houghteling, and Prof. Patrick Fitzgerald for their great and helpful feedback.