Simple Quantum Visualizations using IDL by Rob Dimeo at the NIST Center for Neutron Research provides a nice gateway for a researcher to begin exploring visualizations in quantum mechanics:

This book is not intended to be used as a textbook in IDL programming or quantum mechanics. Rather it can be used as a supplement to a quantum mechanics course or even as a vehicle for a researcher to wade gently into IDL programming in a topic with which he/she is already familiar before embarking on a specific research application involving computing.

I wish a resource like this had been available when I was taking quantum mechanics. Visualizations provide another route to understanding, particularly when you have the source code for them, making it possible to explore your own modifications.

A PDF of the book is available as a free download. Also, check out the other IDL resources available on Rob’s site, including two lengthy PDFs on application development in IDL with example code, as well some genetic algorithm code.

These visualizations of vessel movements, i.e., the movements of ships near port, demonstrate an interesting technique for showing particle movements. From the abstract:

Our visualization is based on density fields that are derived from convolution of the dynamic vessel positions with a kernel. The density fields are shown as illuminated height maps. Combination of two fields, with a large and small kernel provides overview and detail. A large kernel provides an overview of area usage revealing vessel highways. Details of speed variations of individual vessels are shown with a small kernel, highlighting anchoring zones where multiple vessels stop. Besides for maritime applications we expect that this approach is useful for the visualization of moving object data in general.

The original paper is also available. Link via visual complexity.

NodeBox is an application to create 2-dimensional visualizations using Python as a scripting language. It’s similar to the Processing environment that I’ve mentioned before. It seems to be used more for art than “visualization analysis”, but the results are fun to look at.

I’ve used IDL to create a few desktop backgrounds—being able to write code to produce art like this intrigues me.

I have been meaning to mention the recreating movement website for a while. The site has many fascinating examples of visualizing the frames of an animation in different ways including a Shockwave demo so that you can play around with it.

Link via infosthetics.

Some good advice for designing scientific posters:

The best general advice I can give a first-time poster constructor is to describe the circumstances in which a poster will eventually be viewed: a hot, congested room filled with people who are there primarily to socialize, not to look at posters. Because poster sessions are often concurrent with the “wine and beer” mixer, chaos is further increased by hundreds of uninhibited graduate students staggering around hitting on each other. It’s not a pretty sight.

If you use Keynote on a Mac, note that Apple has published some great templates.

Link via BoingBoing.

Robin Sloan’s great short story “Mr. Penumbra’s Twenty-Four-Hour Book Store” opens up the science-fiction/data visualization genre. I just wish there was a 24-hour bookstore around here.

Link via BoingBoing.

Hans Rosling has another engaging TED presentation, “Let my dataset change your mindset”. Rosling uses Gapminder to tell compelling stories about world health. Never are scatter plots so fascinating as in a Rosling presentation!

Manuel Lima at VisualComplexity outlined a Information Visualization manifesto (with later comments) last week. The basic points are:

1. Form follows function
2. Start with a question
3. Interactivity is key
4. Cite your source
5. The power of narrative
6. Do not glorify aesthetics
7. Look for relevancy
8. Embrace time
9. Aspire for knowledge
10. Avoid gratuitious visualizations

Only the first point seems to be controversial, as people have argued that form should follow data. The idea behind these points is to distinguish between what Lima calls information visualization (while Kosara suggestions visual analysis) and information art.

I was hoping to go to VisWeek 2009 next month where this is sure to drawn some conversations, but it looks like I will not be able to make this year.

Wired recently posted “Best Science Visualization Videos of 2009”. It honors the top 10 entries of this year’s SciDAC visualization contest (last year, Tech-X’s entry was in the top 10). From the article:

Some of the most impressive images in science are produced when researchers take numerical data and represent it visually through modeling and computer graphics. The Department of Energy honored 10 of this year’s best scientific visualizations with its annual SciDAC Vis Night awards, at the Scientific Discovery through Advanced Computing conference (SciDAC) in June. Researchers submitted visualizations to the contest, and program participants voted on the best of the best. From earthquakes to jet flames, this gallery of videos and images show how beautiful (and descriptive) visual data can be.

Congratulations to this year’s winners!

Information is Beautiful has a round up of some of the great visualizations available in the Transparency section of Good Magazine. They also have a full gallery of the infographics on Flickr (there are currently 85 images in the set going back to December 2006).

I liked the idea of a Flickr set of visualizations that I made one of my own. Not too much in it yet, but I’ll keep adding to it.