How Good Can Visualization Get?
by Ryan FreitasAs a fan of good information design, I’ve made a point lately of raving about Google Reader’s trends visualization. Despite my enthusiasm for visualizations of personal data from digital life, I admit to some serious data-envy for the exhaustive analog efforts of Nicholas Felton (of NYC design firm Megafone) and his Feltron Annual Report(s).
I’ve been eagerly anticipating the 2006 Feltron report since I first discovered last year’s, and I was not at all disappointed. From the total number of air miles traveled to a geographical listing of every restaurant eaten at in New York City in the past year, the Feltron reports stand as the most gorgeous representation of personal information I’ve ever seen. The extent to which Felton goes to record his own movements along various axes over such a long timeline is incredible, and the quality of execution — especially typographically — is close to perfect.
The quality of Felton’s work has gotten me thinking about improving personal data visualization in the tools we build.
When Adaptive Path founder (and current Googler) Jeff Veen posted recently about the work he and his team had done with Google Reader’s trends, he expressed excitement for “collecting and understanding the ambient information that flows through our digital lives.” Specifically, he referenced an excellent post by Tom Coates, who elaborates on the value of personal data summaries:
… more specifically I don’t want to know this stuff, I want to be able to capture it invisibly so that it can be knitted together and sense made of it and data made discoverable and searchable at some point in the future, when the urge or need takes me.
For me, Tom’s sentiment (and Jeff’s enthusiasm) clarify something I’ve just started to really grapple with: As we create tools that have the ability to record the wakes of users moving through their digital lives, there is a corresponding obligation to create quality visualizations of that data.
Designers should seek to enable everyone to discover meaning in the patterns of the everyday. What is required is something as complete and concise as it is visually parsable — maybe even beautiful. As artifacts go, the Feltron reports are an exemplar that tools like Google Reader Trends should evolve towards, if not in form, than in spirit.
January 22nd, 2007 at 9:36 am
Great post! I agree that we should “enable everyone to discover meaning in the patterns of the everyday.”
However, it may not be enough to leave this job to Interaction Designers. There are too few of us! This is a very large task, and the challenge grows every day as more and more information is digitized, tracked and recorded.
Embedding better visualization tools within popular office or web productivity tools is a good idea. However, I am attempting to take the opposite approach.
By creating a generic visualization product, that leverages the ubiquitous spreadsheet, maybe we can empower people to discover their own meaning. The advantage here is that their data and creativity are not limited by the application that contains a cool visualization.
Certainly, the result will not be as striking or captivating as the work done by Feltron or Google. But if the end goal is to promote understanding of everyday information, why not arm everyone with powerful, flexible and easy to use visualization tools?
-Jeff Carpenter
http://www.agilegraph.com
January 22nd, 2007 at 11:40 am
[...] I recently found the Feltron Report by way of Adaptive Path. It’s a report outlining Nicholas Felton’s activities this year, which is not a horribly engaging topic. However, I read through every page of the report. Feltron has taken mundane details about his life and made something that is quite nteresting. [...]