A simple, interactive means for seeing connections between demographics, diseases, and diagnoses:
We just finished developing this project for GE as part of the launch of their new health care initiative. With the input and guidance of a handful of departments within the company, we began by looking at their proprietary database of 14 million patient records looking for ways to show connections between related conditions. For instance, we wanted visitors to the site to be able to learn how diabetes diagnoses increase along with obesity, but convey it in a manner that didn’t feel like a math lesson. By cycling through the eight items at the top (and the row beneath it), you can make several dozen comparisons, highlighting what’s found in actual patient data. At the bottom, some additional background is provided based on various national health care studies.
I’m excited to have the project finished and online, and have people making use of it, as I readjust from the instant gratification of building things one day and then talking about them the next day. More to come!
Depicting networks (also known as graphs, and covered in chapters 7 and 8 of Visualizing Data) is a tricky subject, and too often leads to representations that are a tangled and complicated mess. Such diagrams are often referred to with terms like ball of yarn or string, a birds nest, cat hair or simply hairball.
It’s also common for a network diagram to be engaging and attractive for its complexity (usually aided and abetted by color), which tends to hide how poorly it conveys the meaning of the data it represents.
On the other hand, Tamara Munzner is someone in visualization who really “gets” graphs in greater depth. A couple years ago she gave an excellent Google Tech Talk (looks like it was originally from another conference in ‘05), titled “15 Views of a Node Link Graph” (video, links, slides) where she discussed a range of methods for working viewing graph data, along with their pros and cons:
A cheat sheet of the 15 methods:
Animated Radial Layouts
Multilevel Call Matrices
2D Hyperbolic Trees
The presentation is an excellent survey of methods, and highly recommended for anyone getting started with graph and network data. It’s useful food for thought for the “how should I represent this data?” question.
I was in the midst of starting a new post in January so I failed to make a post about it at the time, but Oblong’s Tamper installation was on display at the 2009 Sundance Film Festival. John writes (and I copy verbatim):
Our Sundance guests — who already number in the thousands — find the experience exhilarating. A few grim cinephiles have supplementally raised an eyebrow (one per cinephile) at the filmic heresy that TAMPER provides: a fluid new ability to isolate, manipulate, and juxtapose (rudely, say the grim) disparate elements (ripped from some of the greatest works of cinema, continue the grim). For us, what’s important is the style of work: real-time manipulation of media elements at a finer granularity than has previously been customary or, for the most part, possible; and a distinctly visceral, dynamic, and geometric mode of interaction that’s hugely intuitive because the incorporeal suddenly now reacts just like bits of the corporeal world always have. Also, it’s glasses-foggingly fun.
I mostly find this fascinating having not seen it properly depicted, but the interactive version shows more about locations of power plants, plus maps of solar and wind power along with their relative capacities.
I love the craggy beauty of the layered lines, and appreciate the restraint of the map’s creators to simply show us this amazing data set.
And if you find yourself toe tapping and humming “we gonna rock down to…” later this afternoon, then I’m really sorry. I’m already beginning to regret it.
I’ve not been working on Windows much lately, but while installing Windows XP today, I was greeted with this fine work of nonfiction, which reminds me why I miss it so:
So I can’t synchronize the time because…the time on the machine is incorrect. And not only that, but my state represents a security risk to the time synchronization machine in the sky.
I hope the person who wrote this error message enjoyed it as much as I did. At least when writing bad error messages in Processing I have some leeway for making fun of the situation (hence the unprofessional window titles of some of the error dialogs).
Reader Eric Mika sent a link to the video of Obama’s speech that I mentioned a couple days ago. The speech was knocked from the headlines by news of Arlen Specter leaving the Republican party within just a few hours, so this is my chance to repeat the story again.
Specter’s defection is only relevant (if it’s relevant at all) until the next election cycle, so it’s frustrating to see something that could affect us for five to fifty years pre-empted by what talking heads are more comfortable bloviating about. It’s a reminder that with all the progress we’ve made on how quickly we can distribute news, and the increase in the number of outlets by which it’s available, the quality and thoughtfulness of the product has only been further undermined.
Update, a few hours later: it’s a battle of the readers! now Jamie Alessio passed along a high quality video of the the President’s speech from the White House channel on YouTube. Here’s the embedded version:
Author Ben Fry will be presenting “Computational Information Design” –a mix of his work in visualization and coding plus a quick introduction to Processing. We are very excited to talk to Mr. Fry and our thanks go out to this event’s sponsors: Atalasoft and Snowtide Informatics.
Visualizing Data is my book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. Unlike nearly all books in this field, it is a hands-on guide intended for people who want to learn how to actually build a data visualization.
The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)
The book covers ideas found in my Ph.D. dissertation, which is basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.
The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).
This site is used for follow-up code and writing about related topics.