Apropos of today’s posting of the updated Salary vs. Performance piece comes word in the New York Times that a film version of Moneyball has been shelved:
Just days before shooting was to begin, Sony Pictures pulled the plug on “Moneyball,” a major film project starring Brad Pitt and being directed by Steven Soderbergh.
Yesterday I found it far more unsettling that such a movie would be made period, but today I’m oddly curious about how they might pull it off:
What baseball saw as accurate, Sony executives saw as being too much a documentary. Mr. Soderbergh, for instance, planned to film interviews with some of the people who were connected to the film’s story.
I guess we’ll never know, since other studios also passed on the project, but that’s probably a good thing.
As an aside, I’m in the midst of reading Liar’s Poker (another by Moneyball author Michael Lewis) and again find myself amused by his ability as a storyteller: he reminds me of a friend who can take the most banal event and turn it into the most peculiar and hilarious story you’ve ever heard.
I’ve just posted the updated version of Salary vs. Performance for the 2009 baseball season. I had hoped this year to rewrite the piece to cover multiple years, have a couple more analysis options, and even to rebuild it using the JavaScript version of Processing (no Java! no plug-in!), but a busy spring has upended my carefully crafted but poorly implemented plans.
Meanwhile, my inbox has been filling with plaintive comments like this one:
Will you be updating this site for this year? It’s the first year I think my team, the Giants would have a blue line instead of a red line.
How can I ignore the Giants fans? (Or for that matter, their neighbors to the south, the Dodgers, who perch atop the list as I write this.)
More about the project can be found in the archives. Visualizing Data explains the code and how it works, and the code itself is amongst the book examples.
Passed along by Jane Nisselson, a photo she found in the New Yorker, apropos of my continued fascination with command centers and the selection of information they highlight:
I think it was those clocks and choice of cities that were memorable. It is actually One Police plaza and not the terrorism HQ on Coney Island. The photographer is Eugene Richards.
For New Yorker readers, the original article is here.
There’s simply no way to give people access to others’ private records — in the name of security or otherwise — and trust those given access to do the right thing. From a New York Times story on the NSA’s expanded wiretapping:
The former analyst added that his instructors had warned against committing any abuses, telling his class that another analyst had been investigated because he had improperly accessed the personal e-mail of former President Bill Clinton.
This is not isolated, and this will always be the case. From a story in The Boston Globe a month ago:
Law enforcement personnel looked up personal information on Patriots star Tom Brady 968 times - seeking anything from his driver’s license photo and home address, to whether he had purchased a gun - and auditors discovered “repeated searches and queries” on dozens of other celebrities such as Matt Damon, James Taylor, Celtics star Paul Pierce, and Red Sox owner John Henry, said two state officials familiar with the audit.
The NSA wiretapping is treated too much like an abstract operation, with most articles that describe it overloaded with talk of “data collection,” and “monitoring,” and the massive scale of data that traffics through internet service providers. But the problem isn’t the computers and data and equipment, it’s that on the other end of the line, a human being is sitting there deciding what to do with that information. Our curiosity and voyeurism leaves us fundamentally flawed for dealing with such information, and unable to ever live up to the responsibility of having that access.
The story about the police officers who are overly curious about sports stars (or soft rock balladeers) is no different from the NSA wiretapping, because it’s still people, with the same impulses, on the other end of the line. Until reading this, I had wanted to believe that NSA employees — who should truly understand the ramifications — would have been more professional. But instead they’ve proven themselves no different from a local cop who wants to know if Paul Pierce owns a gun or Matt Damon has a goofy driver’s license picture.
Adobe Illustrator has regressed into talking back like it’s a two-year-old:
Asked for further comment, Illustrator responded:
CANT DO THAT. MOMMY NOOOOOO! CANT!
No doubt this is my own fault for not having upgraded to CS4. I’ll wait for CS5 when I can shell out for the privilege of using 64-bits, maybe the additional memory access will allow me to open files that worked in Illustrator 10 but no longer open on newer releases because the system (with 10x the RAM, and 5x the CPU) runs out of memory.
Casey wrote with more info regarding the previous post about Pelham. The command center in the movie is fake (as expected), because the real command center looks too sophisticated. NPR had this quote from John Johnson (spelling?), New York City Transit’s Chief Transportation Officer:
“They actually … attempted to downplay what the existing control center looks like, because they wanted to make it look real to the average eye as compared to… we’re pretty Star Trekky up in the new control center now.”
So that would explain the newish typeface used in the image, and the general dumbing-down of the display. The audio from the NPR story is here, with the quote near the 3:00 mark.
This is the only image I’ve been able to find of the real command center:
Links to larger/better/more descriptive images welcome!
Is this a real place? Buried within the bowels of New York City? And Mr. Washington, how about using one of your two telephones to order a new typeface for that wall? Looks like a hundred thousand dollars of display technology being used for ASCII line art.
Last week at the CaT conference, I met Sheena Matheiken, a designer who is … I’ll let her explain:
Starting May 2009, I have pledged to wear one dress for one year as an exercise in sustainable fashion. Here’s how it works: There are 7 identical dresses, one for each day of the week. Every day I will reinvent the dress with layers, accessories and all kinds of accouterments, the majority of which will be vintage, hand-made, or hand-me-down goodies. Think of it as wearing a daily uniform with enough creative license to make it look like I just crawled out of the Marquis de Sade’s boudoir.
Interesting, right? Particularly where the idea is to make the outfit new through the sort of forced creativity that comes from wearing a uniform. But also not unlike the dozens (hundreds? thousands?) of other “I’m gonna do x each day for 365 days” projects, where obsessive compulsive types take a photo, choose a Pantone swatch, learn a new word, etc. in celebration of the Earth revolving about its axis once more. Yale’s graduate graphic design program even frequents a yearly “100 day” project along these lines. (Don’t get me wrong–I’m happy to obsess and compulse with the best of them.)
But then it gets more interesting:
The Uniform Project is also a year-long fundraiser for the Akanksha Foundation, a grassroots movement that is revolutionizing education in India. At the end of the year, all contributions will go toward Akanksha’s School Project to fund uniforms and other educational expenses for slum children in India.
How cool! I love how this ties the project together. More can be found at The Uniform Project, with daily photos of Sheena’s progress. And be sure to donate.
I’m looking forward to what she has to say about what she’s learned about clothes and how you wear them after the year is complete. Ironic, that the year she wears the same thing for 365 days will be her most creative.
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:
Edge List
Hand-Drawn
Dot
Force-Directed Placement
TopoLayout
Animated Radial Layouts
Constellation
Treemaps
Cushion Treemaps
Themescapes
Multilevel Call Matrices
SpaceTree
2D Hyperbolic Trees
H3
TreeJuxtaposer
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. People who have purchased the book can find the examples here.
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. but applies them to a series of examples, first starting with a simple mapping project (Chapter 3) 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 will be used for follow-up code and writing about related topics.