Four Themes From the Visualized Conference

The first Visualized conference was held in mid-town Manhattan last week. Even with Sandy and a nor’easter, the conference went off with only a few minor hiccups. The idea behind Visualized is a TED-like objective of exploring the intersection of big data, story telling and design. It worked.

Throwing designers and techies together is one of my favorite forums because of what is common and what is different. On one hand, artists are increasingly skilled with technical tools, on the other these people are often coming at things from very different perspectives.

The advantages of mixing these people at Visualized go beyond simple idea sharing.  Each person specializes, leading to amazing expertise, skill, and focused perspective, but also leaving something out. It is not that everyone can learn to do everything, but rather, by sharing projects, methods and tools, we can learn what to ask and who to seek out for collaboration.  The advantages of this mix are that it is the most reliable way to produce projects that evoke emotion with story, design and data to engage and inform.

We were treated to amazing technical talent and creativity, evident in, for example, Cedric Kiefer’s generative dancer reproduction “unnamed soundsculpture.”  To creating the basic model his team started with song, a dancer and knitting together the 3D surface images from three Microsoft Kinect cameras. They re-generated the movie of the dance by simulating the individual particles captured in the imaging and the enhancing these to generate more particles under the influence of “gravity” and “wind” driven by the music.

unnamed soundsculpture from Daniel Franke on Vimeo.

Cedric and his team radically expand ideas of numeric visualization by capturing and building on organic physical data in complex and subtle ways, generating a whole, engrossing new experience from the familiar elements.

Four themes surfaced repeatedly in the ideas and presentations of the speakers:

Teams

Most of the projects were produced by teams made up of people with  a handful diverse skills and affinities. I heard descriptions of teams such as, “we have a designer (color, composition and proportion sense, works in Illustrator, photoshop, pen and paper…), a data scientist (data munging, machine learning, statistical analysis…), a data visualization artist (Javascript, D3 skills, web API mashup skills…) someone who is driven by narrative and story telling (journalist, marketing project lead…), a database guy, etc.”

Assembling and honing these teams of technical and artistic creatives is probably a rare skill in itself and the result is a powerful engine of exploration, creativity and communication.

Hilary Mason from Bit.ly summed up the second-level data scientist talent shortage clearly: “Every company I know is looking to hire a data scientist; every data scientist I know is looking to hire a data artist.”  As broad as data scientists skills are, many are recognizing the value of talented designers with the appropriate programming skills for crafting a clear, engaging message.

The New York Times teams (two different teams presented), the WNYC team of two, Bit.ly, and many others showed the power of teams creating together and bringing diverse talents to projects.

There were a couple of notable individual efforts. My favorite was Santiago Ortiz’s beautiful, complex and functional visualization and navigation of his personal Knowledgebase. His design elegantly uses the 7-set Venn diagram, and his deep insights into searching by category and time come together perfectly.

Journalism

Sniffing out the story is fundamental to projects that evoke emotion with story, design and data to engage and inform. Journalists can smell drama and conflict and ask lots of questions. They have a sense of where to dig deeper. They are able to stick to the thread of the story and a have a valuable work ethic around finding the details and tying up loose ends.

A large part of success of Shan Carter and his team in creating the New York Times paths to the White House win visualization come from their ability to return over and over the the basic idea of making a relevant, accurate and understandable visualization of the various likely outcomes each each of the battleground states.  This visualization went through 257 iterations being checked into their Github repository with a few evident cycles of creative expanding followed by refocusing on the story.

Data Mashups

API-mashup skills found there best examples in the news teams. WNYC’s accomplishments in creating data/visualization mashups to communicate evacuation zones, subway outages, flood zone information updated in real-time during the storms, and other embeddable web widgets was amazing.  While their designs didn’t have the polish of some of the “slower” work presented, they produced great, accurate and timely results in days and sometimes hours.

Design

“A visualization should clarify in ways that words cannot.” (Sven Ehrmann)

This summed up what I found awe-inspiring and satisfying in the design work. Since I primarily work with data visualization, I often rely on the graph-reading skills of my audience rather than optimized design. This may be necessary for many business applications, but when the message is important and the investment you can reasonable expect from your audience is uneven, to take short cuts on design is to completely miss opportunities to engage and inform.  Great designers are masters at creating memory because the are able to reliably create “emotion linked to experience” (Ciel Hunter)

Jake Porway summed up data, team, story and design in the observations section of his presentation:

  • Data without analysis isn’t doing anything
  • Interdisciplinary teams are required
  • Visualization is a process (see the example from Shan Carter at NY Times above)
  • Tools enable amazing outcomes possible with limited resources
  • There is a lot of potential to do a great deal of good with when we learn to evoke emotion with story, design and data to engage and inform.