Making data

30
Lived Informatics John Rooksby

description

Slides from my talk at Making Data, Lancaster University

Transcript of Making data

Page 1: Making data

Lived InformaticsJohn Rooksby

Page 2: Making data

Invited talk at Making Data, Lancaster University, 22-23 Jan 2014.

http://www.lancaster.ac.uk/fass/events/making-data/index.htm

Page 3: Making data

EuroFit: Social innovation to improve physical activity and sedentary behaviour through elite European football

www.Eurofitfp7.eu

A populations approach to ubicomp systems design

www.softwarepopulations.com

Future Cities

Page 4: Making data

CES 2014

Tech for health and fitness a major part of show

Page 5: Making data
Page 6: Making data

SitFIT (artist’s impression)To enable self-monitoring of free-living sedentary behaviour and physical activity. Cumulative sitting time is given context by visualising alongside upright time

Step count Cumulative daily total

Sitting time Cumulative daily total

Upright time Cumulative daily total

Sedentary Behaviour IndexThe index reflects duration of sitting bouts, short bouts are better

Sitting bout timerVibro-tactile feedback tells the wearer how long they have been sitting for

Page 7: Making data
Page 8: Making data
Page 9: Making data

Continuous tracking on high end smartphones

• iPhone 5s• Motorola Moto X Image: engadget

Page 10: Making data

Pass the ball(EuroFit)

Match Fit(EuroFit)

MyCity(institute for health and wellbeing)

Page 11: Making data

Endomondo

The Walk

Moves

Page 12: Making data

MyFitnessPal

Withings

Page 13: Making data

1965

htt

p:/

/ww

w.y

am

asa

-toke

i.co

.jp/t

op_c

ate

gory

/art

icle

_pedom

ete

r_firs

t.htm

l

Page 14: Making data

1965

htt

p:/

/ww

w.y

am

asa

-toke

i.co

.jp/t

op_c

ate

gory

/art

icle

_pedom

ete

r_firs

t.htm

l

Page 15: Making data

1965

htt

p:/

/ww

w.y

am

asa

-toke

i.co

.jp/t

op_c

ate

gory

/art

icle

_pedom

ete

r_firs

t.htm

l

Page 16: Making data

1965

htt

p:/

/ww

w.y

am

asa

-toke

i.co

.jp/t

op_c

ate

gory

/art

icle

_pedom

ete

r_firs

t.htm

l

Page 17: Making data

10000 is culturally significant

http://en.wikipedia.org/wiki/Ten_thousand_years

Page 18: Making data

The subject of walking is, in some sense, how we invest universal acts with particular meanings. Like eating or drinking, it can be invested with wildly different cultural meanings, from the erotic to the spiritual, from the revolutionary to the artistic. Here this history begins to become part of the history of the imagination and the culture, of what kind of pleasure, freedoms and meanings are pursued at different times by different kinds of walks and walkers.

The treadmill … allows travel to be measured entirely by time, bodily exertion, and mechanical motion. Space – as a landscape, terrain, spectacle, experience has vanished.”266

“Like eating or drinking, [walking] can be invested with wildly different cultural meanings, from the erotic to the spiritual, from the revolutionary to the artistic. “ (p3)

“The treadmill … allows travel to be measured entirely by time, bodily exertion, and mechanical motion. Space – as a landscape, terrain, spectacle, experience has vanished.” (p266)

Rebecca Solnit – Wanderlust: A History of Walking

Page 19: Making data

Bill Bowerman, a co-founder of Nike, did not just introduce new forms of running shoes, but developed and popularised new forms of exercise – including jogging.

Technology and activity as mutually articulating

Health science is constituent in but not leading innovation in this area

http:

//en

.wik

iped

ia.o

rg/w

iki/

Bill_

Bow

erm

an

Page 20: Making data

What are people making of fitness

technology?

Interviews with 22 people, with follow ups around a month later

Paper forthcoming CHI’14:Personal Tracking as Lived informaticsRooksby, Rost, Morrison, Chalmers

www.johnrooksby.org/papers/livedinformatics.pdf

Page 21: Making data

• Interviewees used various apps and devices to track – Walking– Physical exercise– Eating and Drinking– Weight and size– Sleep

• They were often tracking several things

Page 22: Making data

• The interviewees were using trackers for– Training and exercise routines– Weight loss and/or maintenance– In order to sleep well – For enjoyment

• Interviewees were often tracking for more than one purpose

• Interviewees could both hate and enjoy tracking– Training, weight loss, etc. can be hard work

Page 23: Making data

• Some trackers used alongside each other, some are integrated– MyFitnessPal a popular “hub”– Integration can be problematic

• Sometimes several trackers with similar or the same functionality were used

• It was common to switch between trackers– Try new ones out– Trackers given as gifts– New phones

Page 24: Making data

Most interviewees did not seek to track everything• E.g. gym visits rarely tracked• Often tracking used to get a sense of routine

One person wanted to track as much as he could but:• “My girlfriend gets annoyed with me for all these

things. ... You know if we’re in bed [my Jawbone UP] is comfortable for me, but it may not be comfortable for her. ... If we’re in a restaurant ... she’s like, you’re allowed thirty seconds and then put [the iPhone] away, cos its rude. “

Page 25: Making data

Tracking was rarely a long term data collection

• Sometimes event to event“Every marathon I’ve done since I got this, I’ve got all the training runs in a folder. I don’t look at them. But at the time, when you’re training for something, [the data is] really important.”

• Sometimes day to day“If I get home at night and I’ve done 7000 I’ll go out and do another 2000. So it’s keeping me on that sort of 10,000 track.”

To track is to look forward

Page 26: Making data

None of the interviewees posted data to social networks• “I don’t know, I find it kind of egotistical ... it’s

almost one of those things where you set yourself up for failure” (P10)

Most knew people who did post to social networks, and could be scathing:• “Pathetic”• “5 whole miles!”

Page 27: Making data

Yet, tracking was often social

Families and couples• Togetherness – e.g. comparing data, or tracking ‘special’

walks• And rows “I said it’s not about walking further than me. It’s

about your own fitness and everything!”

Running partners and workmates sharing data • “I was with her, running all the time, regularly at weekends,

we were running both at the same speed, same distance, we’d keep an eye on this thing together.”

• [Nurses rounds] “So they’d be like, how many steps did we walk? We were kind of using it like a collective. We all discussed it and we’d be like, oh that's shit, heh heh. It’s only that many calories for all we’ve been doing ... But we lost interest ... it was the same day in, day out.”

Page 28: Making data

Implications…

• The design problem is not so much accurate tracking of a pre-given activity, but allowing activities and tracking to co-emerge.

• Don’t expect people to use a single tracker over the long term. Consider how trackers can be interwoven and switched between.

• (Re)consider social tracking, this is not just about sharing on Facebook.

• Don’t assume people want to be data scientists or do analytics – they want to do things like lose weight, run marathons - to look forward, not backward

Page 29: Making data

In Development…

Pass the ball Match Fit MyCity(institute for health and

wellbeing)

Page 30: Making data

Thank you

johnrooksby.org

@johnrooksby