of the most exciting possible things.

You probably guess what they are -- data and history.

Right? So, I'm not a historian.

I'm not gonna give you a definition of history,

but let's think instead of history within a framework.

So when we are making history

or when we are creating historical documents

we are taking things that have happened in the past

and we are stitching them together into a story.

So let me start with a little bit of my own story.

Like anybody my age who works creatively with computers

I was a popular socially well-adjusted young man --

(Laughter)

And sporty! Sporty young man.

And like a lot of people my age

in the kind of business that I'm in

I was influenced tremendously by Apple.

But notice my choice of logo here, right?

The Apple on the left, not the Apple on the right.

I am influenced as much by the Apple on the right

as the next person. But the apple on the left

I mean look at that logo, it's a rainbow --

It's not even in the right order!

That's how crazy Apple was. (Laughter)

But I don't want to talk too much about the company.

I'll start talking about a machine though.

How amazing it is to think about this,

and I go back and I think about this --

Wednesday, one Wednesday when I was

about 12 years old, I didn't have a computer.

On Thursday, I had a computer.

Can you imagine that change?

It's so drastic, I can't even think about anything

that could change our lives that way.

But I'm actually not even going to talk about the computer.

I'm going to talk about a program

that came loaded on that computer.

And it was build by, not the guy on the left,

but the guy on the right.

Does anybody know who the guy on the right is?

Nobody ever knows the answer to this question!

This is Bill Atkinson.

And Bill Atkinson was responsible for tons of things

that you see on your computer everyday.

But I want to talk about one program

that Bill Atkinson wrote called Hypercard.

Yeah -- someone is cheering over there.

(Laughter)

So, Hypercard was a program that shipped with the Mac

and it was designed for users of the computer

to make programs on their computers.

Crazy idea today. And these programs were not

the apps that we think about today

with their large budgets and their big distribution.

These were small things. People making applications

to keep track of their local basketball team scores

or to organize their research

or to teach people about classical music

or to calculate weird astronomical dates.

And then, of course, there were some art projects.

This is my favourite one, it's called 'If monks had Macs'

and it's a non-linear kind of exploratory environment.

I thank the stars for Hypercard all of the time.

And I thank the stars for putting me in this era

where I got to use Hypercard.

Hypercard was the last program to ship

on a public computer, that was designed

for the users of the computer to make programs with it.

If you talked to the people who invented the computer

and you told them there would be a day,

a magical day, when everybody had a computer

but none of them knew how to program,

they would think you were crazy!

So let's get forward a few years.

I'm starting my career as an artist

and I'm building things with my computer --

small scale things. Investigating things

like the growth systems of plants.

Or, in this example, I'm building a simulated economy

in which pixels are trading colour with one another.

Trying to investigate how these types of systems work

and just kind of having fun.

And then this project led me to start working with data.

So I'm building graphics like this,

which compare "communism" -

the frequency of usage of the word "communism"

in the New York Times to "terrorism" at the top.

So you see "terrorism" kind of appears

just as "communism" is going away.

And with these graphics I was really interested

in the aesthetic of the graphs.

So, this is Iran and Iraq, it reads

like a clock, it's called the "timepiece graph"

And this is another timepiece graph

overlaying despair, I think, over hope

and there's only three times -- that's it, crisis

over hope -- There's only three times when crisis

eclipses hope. We are in the middle of one of them

right now -- but don't think about that too much.

(Laughter)

And finally the culmination of this work

with the New York Times' data a few years ago

was the attempt to combine an entire year's

news cycle into a single graphic.

So these graphics actually show us a full year

of news, all the people, and how they are connected

into a single graphic. And, from there

I started to be interested again

in more active systems. So, here's a project

called "Just landed" where I'm looking at people

tweeting on Twitter "Hey! I just landed in Hawaii!"

You know how people just casually try to sneak that

into their twitter conversation. "I'm not showing off!

Really! But I did just land in Hawaii."

And then I'm plotting those people's trips

in the hopes that maybe we can use social network

and the data that it leaves behind

to provide a model of how people move

which would be valuable to epidemiologists

among other people. And, more fun --

this is a similar project looking at people

saying "Good morning!" to each other

all around the world. Which taught me

by the way, that it is true that people

in Vancouver on the West Coast wake up

much later and say "good morning" much later

than the people on the East Coast

who are more adventurous.

Here's a more useful -- maybe -- project

where I took all the information

from the Kepler project and try to put it

into some visual form that made sense to me.

And I should say that everything I've shown you

up to now -- these are all things

that I just did for fun. It may seem weird

but this comes back from Hypercard.

I'm building tools for myself.

I may share them with a few other people

but they are for fun, they are for me.

So all these tools I showed you

that kind of occupy this weird space --

somewhere between science, art and design

and that's where my practice lies.

And still today from my experience with Hypercard

what I'm doing is I'm building visual tools

to help me understand systems.

So today I work at the New York Times --

I'm the data artist in residence at the NY Times --

and I've had the opportunity at the Times

to work on a variety of really interesting projects,

two of which I'm going to share with you today.

The first one I've been working on, in conjunction

with Mark Hansen. Mark Hansen is a professor

of statistics at the UCLA. He's also a media artist.

And Mark came to the Times with a very interesting question

to what may seem like an obvious problem --

When people share content on the Internet, how does

that content get from person A to person B?

Or, maybe person A to person B to person C

to person D. We know that people share content

in the Internet, but what we don't know

is what happens in that gap

between one person to the other.

So we decided to build the tool to explore that

and this tool is called 'cascade'.

So if we look at these systems that start

with one event that leads to other events.

We call that structural cascade.

And these cascades actually happen over time

so we can model these things over time.

Now, the New York Times has a lot of people

who share our contents, so the cascades

do not look like that one, they look more like this --

So here is the typical cascade.

At the bottom left, the very first event.

And then as people are sharing the content

from one person to another we go up

in the Y axis - degrees of separation -

and over on the X axis for time.

So we are able to look at that conversation

in a couple different views. This one

which shows us the threads of conversation.

And this one which combines that stacked view

with a view that lets us see the threads.

Now the Times publishes about seven thousand pieces

of content every month. So it was important for us,

when we were building this tool

to make it an exploratory one.

So the people could dig through this vast terrain

of data -- I think of it as a vehicle

that we are giving people to traverse

this really big terrain of data.

So here is what it really looks like

and here is a cascade playing in real time.

I have to say, this was a tremendous moment.

We had been working with canned data, fake data

for so long, that when we saw this

for the first moment, it was like an archaeologist

who had just dusted off these dinosaur bones.

And we discovered this thing

and we were seeing it for the first time.

These sharing structures that underlie the Internet.

And maybe the dinosaur analogy is a good one

because we are actually making some probabilistic

guesses about how these things link.

So we are looking at some of these pieces

and making some guesses but we try to make sure

that those are as statistically rigorous as possible.

Now, tweets in this case, they become

parts of stories, they become parts of narratives.

So we are building histories here, but they are

very short term histories. And sometimes

these very large cascades are the most

interesting ones, but sometimes the small ones

are also interesting. This is one of my favourites

- we call this "The Rabbi Cascade."

It's a conversation amongst rabbis about this article

in the New York Times about the fact that religious

workers don't get a lot of time off.

I guess Saturdays and Sundays are bad days

for them to take off.

So in this cascade there is a group of rabbis

having a conversation about a New York Times' story.

One of them has the best Twitter name ever --

he's called the 'VelveteenRabbi'.

(Laughter)

But we wouldn't ever found this if it weren't

for this exploratory tool.

This would just be sitting somewhere

and we would have never been able to see that.

But this exercise of taking single pieces

of information and building narrative structures,

building histories out of them,

I find it tremendously interesting.

Now, I moved to New York about two years ago.

And in New York everybody has a story

that surrounds this tremendously impactful event

that happened on September 11th of 2001.

And my own story with September 11th

has really become a more intricate one

because I spent a great deal of time working

on a piece of the 9/11 memorial in Manhattan.

So the central idea about the 9/11 memorial

is that the names in the memorial are not laid out

in alphabetical order, or chronological order,

but instead they are laid out in a way

in which the relationships between the people