Difference between revisions of "Item talk:Q1172"
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| Line 78: | Line 78: | ||
Many things: | Many things: | ||
* intermediate GPS traces | * intermediate GPS traces | ||
| − | * | + | * historic GPS traces |
* log on/log off/available times | * log on/log off/available times | ||
| − | * | + | * speed/policing of driving |
| + | * tags sur tickets | ||
| + | * notifications | ||
| + | * vehicle data | ||
| + | * star rating | ||
| + | * experiment information | ||
| + | * logic of the processing (many "myths"...) | ||
== Easily replicable == | == Easily replicable == | ||
Revision as of 10:46, 4 October 2019
Travail de plateformes et gouvernance algorithmique: quels sont les enjeux?
This page: http://tiny.cc/pdio-unimail
Poster
Introduction
- Paul-Olivier Dehaye (Q351) - on Wikidata
- PersonalData.IO (Q182): "data rights individually actionable and collectively useful"
- Q585: "personal data empowerment"
- MyData Geneva (Q50)
Starting point
- Loss of agency in interactions with the platforms
- individual level: autonomy
- collective level: sovereignty
- Data is an essential resource for the platform
- "operating system for the city" - "système d'exploitation"
- individual agency: "personal data rights"
- collective level: "making data open"
Personal data rights
Definition
personal data (Q28): "data about an identified or identifiable individual"
Rights
- right of access to personal data (Q51): view/get a copy of all our personal data
- right to data portability (Q1209)
- scope: "data provided by the data subject"
- "in a commonly-used, machine readable format", at least from the data controller to the data subject
- "without hindrance, [..] where technically feasible", from one data controller to another directly
- right to information about the logic of the processing (Q1211)
FairTube
- guy has a nice slingshot channel
- gets "demonetized"
- launches Fairtube campaign (Q1212)
- results: "data rights collectively useful"
Uber
London
Geneva
Passenger data
How?
- make a request: see Uber (Q101)
- uses Kepler.gl (open source Uber tool!)
Why?
- "understand my work"
- information (policing of work, through GPS and accelerometers for instance)
- data flow tracing for regulation
- data for labor laws accountability
What is missing?
Frame for addressing the question: model of Uber (simulcast from ConnectedData London)
Many things:
- intermediate GPS traces
- historic GPS traces
- log on/log off/available times
- speed/policing of driving
- tags sur tickets
- notifications
- vehicle data
- star rating
- experiment information
- logic of the processing (many "myths"...)
Easily replicable
For instance Deliveroo (Q102)
Challenge
