Nieman Foundation at Harvard
HOME
          
LATEST STORY
Newsonomics: The New York Times restarts its new-product model, in Spanish
ABOUT                    SUBSCRIBE
June 26, 2014, 4:51 p.m.
Aggregation & Discovery
LINK: bost.ocks.org  ➚   |   Posted by: Liam Andrew   |   June 26, 2014

Mike Bostock is one of data visualization’s leading lights. As creator of the hugely popular visualization library D3.js and editor in The New York Times’ graphics department, he has had a hand (visibly and invisibly) in most of the widely shared interactives on the web.

Today Bostock posted an adaptation of a celebrated talk he gave at Eyeo 2014 about visualizing algorithms. Full of ideas and gorgeous patterns, it’s an elegant flip to the script of the typical data visualization.

Computers are sometimes conceptually divided between data structures and algorithms, and we usually visualize the data, while ignoring the processes that manipulate it. But Bostock argues that “visualization is more than a tool for finding patterns in data.”

He breaks down various methods for sampling, shuffling, sorting, and making mazes, ably explaining (via text and gorgeous graphics) why there are different types of randomness, for example, or how to most effectively sort a list.

bostock-quicksort

Bostock is interested in the value of visualizing algorithms for learning about and understanding complex processes. A novice could use a visualization to peer into an algorithm’s black box; an expert algorithm builder might visualize in order to debug and reframe it.

He classifies algorithm visualizations based on the level of introspection they give into the data — some only show the output, while others let you peer fully into how data points are being manipulated.

The goal here is to study the behavior of an algorithm rather than a specific dataset. Yet there is still data, necessarily — the data is derived from the execution of the algorithm. And this means we can use the type of derived data to classify algorithm visualizations.

Using his work on the Times’ revamped rent-versus-buy calculator as an example, he shows how opening up the algorithm allows for new questions:

To output an accurate answer, the calculator needs accurate inputs. While some inputs are well-known (such as the length of your mortgage), others are difficult or impossible to predict. No one can say exactly how the stock market will perform, how much a specific home will appreciate or depreciate, or how the renting market will change over time.

We can make educated guesses at each variable — for example, looking at Case–Shiller data. But if the calculator is a black box, then readers can’t see how sensitive their answer is to small changes.

To fix this, we need to do more than output a single number. We need to show how the underlying system works.

rent-vs-buy

Some of the examples are fairly technical and outwardly trivial — in a sense, what are the social implications of a sorting algorithm as long as the sorting happens? But they do demonstrate the sheer number of ways to solve a seemingly simple problem, and in the case of some of these examples (such as sampling algorithms), the results matter immensely.

The examples also demonstrate an opportunity to rethink what a visualization can tell us. Whether static or dynamic, or whether describing a state or a process, a visualization can show and hide as much as it needs.

Show tags Show comments / Leave a comment
 
Join the 15,000 who get the freshest future-of-journalism news in our daily email.
Newsonomics: The New York Times restarts its new-product model, in Spanish
After a few expensive misfires, the Times is building new products on a smaller, more targeted scale.
En Español: The New York Times launches a Spanish-language news site aiming south of the border
The New York Times en Español is the Times’ latest attempt to grow its audience internationally.
The New York Times’ new Slack 2016 election bot sends readers’ questions straight to the newsroom
“Instead of asking you to come to us and be part of this massive room of people shouting over each other, you can bring us to you, and have us be, essentially, one more person in your conversation.”
What to read next
0
tweets
Out of many, NPR One: The app that wants to be the “Netflix of listening” gets more local
A big update moves NPR One yet another step in the direction of becoming a one-stop shop for all audio content, from local newscasts to podcasts outside the NPR world.
0Need to find, keep, and maximize talent today? Look to an old-school example, Gene Roberts
“Virtually every hire should be part of a long-range master plan of journalistic excellence.”
0The New York Times and WBUR are bringing ‘Modern Love’ essays to life with sounds and celebrity reads
“We’re trying to touch people just through sound, in a really profound way.”
These stories are our most popular on Twitter over the past 30 days.
See all our most recent pieces ➚
Fuego is our heat-seeking Twitter bot, tracking the links the future-of-journalism crowd is talking about most on Twitter.
Here are a few of the top links Fuego’s currently watching.   Get the full Fuego ➚
Encyclo is our encyclopedia of the future of news, chronicling the key players in journalism’s evolution.
Here are a few of the entries you’ll find in Encyclo.   Get the full Encyclo ➚
Voice Media Group
Seattle Post-Intelligencer
Mozilla
Kickstarter
PBS NewsHour
The Seattle Times
Twitter
Semana
U.S. News & World Report
Bureau of Investigative Journalism
West Seattle Blog
INDenverTimes