Data Sense: People's Engagement with Their Personal Digital Data
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Transcript of Data Sense: People's Engagement with Their Personal Digital Data
Data Sense: People’s Engagement with Their Personal
Digital Data
Deborah LuptonNews & Media Research Centre
Faculty of Arts & DesignUniversity of Canberra
Living Digital Data research program
• How to people use and conceptualise their personal digital data?
• What do they know of how their data are used by others?
• How do they use other people’s data?• What are the intersections of lively devices, lively
data and human life itself?
Perspectives
sociomaterialism
critical data studies
cultural geography
sensory studies
digital anthropology
digital sociology
The 13 ‘Ps’ of big data
Portentous (momentous discourse)Perverse (ambivalence)Personal (about our everyday lives)Productive (generate new knowledges + practices)
The 13 ‘Ps’ of big data
Partial (tell a particular narrative, leave stuff out)Practices (involve diverse forms of action)Predictive (used to make inferences)
The 13 ‘Ps’ of big data
Political (reproduce power relations + inequalities)Provocative (scandals + controversies)Privacy (how personal data are used/misused)Polyvalent (contextual, many meanings)Polymorphous (materialised in many forms)Playful (can be fun/pleasurable)
The vitality of digital devices
lively devicesmobile
ubiquitous
companions
co-habitants
embodied
The vitality of digital data
lively data
data about life
social lives of data
data impacts on life
data livelihood
s
Data and emotion
data visceralisation
data pleasure
data frustratio
n
data betrayal
data boredom
data mystery
data fear
Data sense
data sense
digital sensor
s
human senses
sense-making
Cycling Data Assemblages project
human
bicycle
digital device
digital datahuman senses
emotion
space/place
Data collection for Cycling Data Assemblages Project
1. Interview 1 (talk to participant about their self-tracking and cycling practices)
2. Enactment of participant getting ready for a ride and finishing a ride
3. Go Pro footage of ride4. Interview 2 (talk to participant about the Go Pro
footage and the self-tracked data they collected on their ride)
Participant shows how he gets ready for a ride
Participant shows and talks about his cycling data on his phone app
Participant shows and talks about his cycling data on his computer screen
Preliminary findings
Self-tracked data …
– offer ‘objective’ measures over ‘subjective’ embodied sensations
– ‘documented proof’ that a ride took place and how long and fast it was
– can monitor changes in fitness over time– can be social– can tell you if you are struggling or feeling good– need to be assessed against previous experiences
Preliminary findings
Self-tracked data …
– can be motivating – ‘external validation’– knowing speed ‘makes me work harder’– distance travelled ‘gives a sense of achievement’– seeing heart rate ‘tells me how much work I’m doing’– can only tell you so much about a ride (can’t access
the ‘internal battles’ or incorporate traffic or weather conditions or impact of different bikes)
Preliminary findings• Self-tracked data …
– value of data can mean less caution about data privacy– makes you more aware of parts of the ride (e.g. Strava
‘segments’)– assists riding technique (noticing speed, anticipating gear
changes)– can change the way you feel about your body– helps explain why you felt a certain way about a ride– reminds you of how you felt during the ride