Data as a Creative Material

DATA AS A CREATIVE MATERIAL

FFunction

Sébastien Pierre + Audrée Lapierre Collide

Halifax, October 23rd, 2014

Information Design & Data Visualization Studio founded in 2008

FFunction

Data As a Creative Material

About this talk



Art Design

Communication


Thought Experience &

ART & DATA

PART I

Art and Data

Ellsworth Kelly, The Meschers, 1951 (oldest reference in Wikipedia's “generative art” entry)

Art and Data

Frieder Nake, Walk-through-Raster, series 2, 1-4 See 20-20 digital hindsight. Frieder Nake, Walk-through-Raster,

series 2, 1-4, C-type print, Germany, 1966. © artist. Photo: V&A Images.

Art and Data

Ryoji Ikeda, Datatron, 2008

Art and Data

THE PROCESS AND THE RESULT

Automation (in art) was a paradigm shift. The result is determined by a process, but unknown to the artist

before the process is complete.

Jared Tarbell, Substrate 2003

Art and Data

Variation in output from Jared Tarbell, Substrate 2003

Art and Data

Jared Tarbell, Orbitals 2004

Art and Data

Jared Tarbell, Invader Fractals 2003

Art and Data

MACHINE CO-CREATION

The result is the act of co-creation between the artists/programmers and

the machine.

Art and Data

“Set an algorithm and let it go”

Dextro

turux.org

Art and Data

Subblue, Fractals, www.subblue.com/

Art and Data

http://www.subblue.com/

Robert Hodgin, Stippling, vimeo.com/8252908

Art and Data

http://vimeo.com/8252908

AESTHETICS OF COMPLEXITY

The amount of details permitted by computers lead to an aesthetics

of complexity.

Art and Data

MACHINE & ORGANICS

Interestingly, some works give the impression of being the product of

a natural process, reconciling technology & natural life

Art and Data

Michael Hansmeyer, Digital Grotesque

Art and Data

Christoph Bader, https://www.flickr.com/photos/deskriptiv

Art and Data

Nervous Systems, Hyphae Lamp

Art and Data

SWAPPING RANDOM NUMBERS FOR DATA

Data is sampled from our environment. It is a byproduct of

human/natural activity.

Art and Data

Art and Data

Ben Fry, All Streets, 2008

Art and Data

Paul Butler, Visualizing Friendships, 2010

COMPLEX & MEANINGFUL

Data has the same complex quality as random numbers do, but there

is a potential for meaning & insights.

Art and Data

A MIRROR OF OURSELVES

As a reflection of ourselves & our complex social fabric, data adds a

new dimension to the resulting artwork.

Art and Data

H OW THE D ATA LAN DS CAP E EVO LVED

PART I I

How the Data Landscape Evolved

1990 20002010

Volume of data Ease of working with data



1990 20002010

Random Numbers

Feeding more numbers in algorithms to increase complexity


Design by Numbers, John Maeda (MIT), Late 90s



1990 20002010

Geographic & Scientific Data

Visuals can be used to reveal things about our environment.


Line Drops, David Endelman, 1997

“The lines in this image are of hundreds of underground and underwater pipelines that draw oil

from a reservoir in the Huntington Beach area of California”



1990 20002010

Web 2.0 APIs

User-generated is published en-masse. Tagging creates new ways to organize content. RSS & APIs made content machine-accessible.


Revealicious, Sébastien Pierre, 2005



1990 20002010

Social Networks & Media

Data about large-scale communities and conversation is now available


Vister, Jeffrey Heer & Danah Boyd, 2005



1990 20002010

Open Data

Citizens can understand and map how the governments work and perform services.


DataViva, 2014


The volume of available data grew significantly over the

past decade

More Data!


Data is more accessible (data portals, APIs) and tools make it

easier to use and visualize.

Easier to access and use


With social networks, social media and open-data we have immediate access to a lot of

information to understand our society.

Data to understand our society


With democratization of infographics, data-journalism & public datasets, data is not reserved

to scientists and specialists anymore.

Data for everyone

CO M MU N ICATI NG D ATA

PART I I I

Similar diversity, Philipp Steinweber & Andreas Koller, 2001

Communicating Data

# Practical tips

Communicating Data

#1 DATA IS NOT INFORMATION

Data needs context to be interpreted and turned to

information.

Communicating Data

Communicating Data

#2 DATA CALLS FOR (VISUAL) SUMMARIES

Visuals and statistics allow to make the data digestible

Communicating Data

#3 DATA = FACTS (FOR A LOT OF PEOPLE

Numbers have an authority that words don’t have.

Communicating Data

Communicating Data

#4 VISUALS ARE THE MESSAGE

The way you choose to represent the data defines how people will

read it.

Communicating Data

HEADLINE “Obama undid the mess left by the previous administration”

HEADLINE “Just as many jobs were lost during the Bush years as during the Obama years”

Communicating Data

#5 DATA MAY NOT MATCH YOUR STORY

Data won’t necessarily tell the story you would like it to tell (but you can always tweak the charts)

Communicating Data

#6 DATA OPENS UP DIALOGUE (AND CRITICISM)

As there’s not a single unique way to interpret data, using data

means you open up to a conversation.

Communicating Data

Same dataset, three different interpretations

Data: Spending of the global middle-class, 2009-2030

Communicating Data

#7 DATA LEADS TO NEW NARRATIVE FORMS

Showing data means that you won’t be able to explain

everything, and will let some of the story be written by the reader.

THE VIS U ALIZAT I O N S P EC TRUM

PART IV

The visualization spectrum



Start Here


Start Here


Exploration Narration











EXPLORATION

PROS

+Discovery +Free progression & exploration

CONS

-Little control -Could miss important things

NARRATION

PROS

+Controlled experience & messaging +Progressive introduction

CONS

-Experts might not like it -Reduced opportunity for new insights

DATA VI SUALIZAT I O N F R OM

T HE TR ENCHE S

PART V

Data Visualization From the Trenches

National Geographic Explorers

Database for researchers

National Geographic projects portfolio

Free exploration for experts and newcomers

Promote the explorers


Video of first versions

Where Do I Start?


Where Am I?

nationalgeographic.com/explorers/projects/

http://www.nationalgeographic.com/explorers/projects/


!

Cool visuals are not enough


HP Earth Insights


The Project

The 16 Earth Insights sites

Analysis

Wildlife Picture Index

Species

Trap camera pictures of species

1 2 3

From concrete to abstract


1 2 3

From concrete to abstract

3

earthinsights.org

http://www.earthinsights.org

3


It’s My Life! Stop Cancer Before It Starts


Lay-friendly platform to complement annual report

Canadian Cancer Society Interactive Tool

Educate, engage and empower Canadians

Shareable & asset for influencers


Cancer & Me

Why should I care?

The Burden

Canadian cancer %

My Lifestyle

User’s life habits Prevention messaging

1 2 3

Pledge

Change in Behavior & Sharing

4

Content & Structure

itsmylife.cancer.ca

http://www.itsmylife.cancer.ca


34% were return visitors

Users spent 4:03 perusing the website

26% bounce rate vs 70% for cancer.ca

20% boost in social media shares

18% pledged to change their behaviour

http://cancer.ca


W HAT’S N E X T

PART VI

What’s Next

Many Devices, Many sizes Desktop, laptop, mobile phone, table and interactive screens... How do we create visualizations that work across this wide range of supports?

What’s Next

How do I relate to the data, how does it relate to me? With some of the novelty wearing out, how do we make data interesting, and how to we adapt this data to the user?

Data

You

What’s Next

Quantified Self & Internet of Things Data The quantity of data available about us, individually, is going to increase significantly with the new breed of devices coming in. This not only raises design questions, but ethical questions as well.

What’s Next

What’s Next

Data for Good With Open Data, citizens can get involved and use data to influence and change society. Data can now be use to solve problems... and maybe help expose corruption?

What’s Next

Burak Arikan, Networks of Dispossession http://istanbul-urban-research.blogspot.ca/2014/01/networks-of-dispossession.html

http://istanbul-urban-research.blogspot.ca/2014/01/networks-of-dispossession.html