3 ms·

Depends on the granularity of the data. What's wrong with (say) 100m square blocks as spatial granularity, with ride time to the nearest minute or even 5 minute

Depends on the granularity of the data. What's wrong with (say) 100m square blocks as spatial granularity, with ride time to the nearest minute or even 5 minutes. The city should be able to ensure regulatory compliance, while anonymity is preserved.

SilasX 7y ago
In dense urban areas, there are probably a lot of scooters within a 100m x 100m block.
- sokoloff 7y ago
  I think that's the point of the suggestion.
  - SilasX 7y ago
    The "point" was to ensure privacy while satisfying the other desiderata of the the system, which includes ability to find a distinct scooter. I was disputing that it met the latter criteria by grouping too many scooters together (Scylla) in its attempt to avoid privacy violation (Charybdis). After all, why not just lump scooters into the east vs west coast? Though I grant the general point that making the drop-off location more granular could satisfy both criteria, but you would need some kind of varying size to account for scooter density.
    - steve_gh 7y ago
      If you can count how many scooters are in the system at any time (and how many belong to different providers) then you should be able to enforce your licencing regime. And if you know roughly where rides are going to / from and when, then that helps you integrate your different types of public transport - for example making sure that when the train arrives there are enough scooters there, or understanding how popular scooter ride paths interact with bike lanes, bus lanes, etc. Mobile phone cell size is generally a pretty good proxy for population density - modern micro-cell sectors can be pretty small, and 5G will make them even small in urban areas. (I work on this sort of stuff for a major engineering data science and asset management group in the UK).
    - malandrew 7y ago
      > which includes ability to find a distinct scooter I understand why a company needs to find a distinct schooter, but why does the city need the ability to find a distinct scooter?
morganherlocker 7y ago
This would not provide very much privacy protection at all. Almost all trips will be unique with this level of granularity, so it will be easy to de-anonymize. I do privacy research with this type of data and have found numerous sources that used aggregation schemes with similar levels of granularity. In those public datasets, I was able to identify trips moving between a high school and a local planned parenthood, for example. 100m is far smaller than the size of school campus and most buildings. To address privacy issues, data needs to be aggregated, with trip clusters with less than 5-10 trips dropped. Differential privacy strategies also exist, but dropping groups with low number of user contributions is the easiest solution to implement.

SilasX 7y ago

In dense urban areas, there are probably a lot of scooters within a 100m x 100m block.

sokoloff 7y ago
I think that's the point of the suggestion.
- SilasX 7y ago
  The "point" was to ensure privacy while satisfying the other desiderata of the the system, which includes ability to find a distinct scooter. I was disputing that it met the latter criteria by grouping too many scooters together (Scylla) in its attempt to avoid privacy violation (Charybdis). After all, why not just lump scooters into the east vs west coast? Though I grant the general point that making the drop-off location more granular could satisfy both criteria, but you would need some kind of varying size to account for scooter density.
  - steve_gh 7y ago
    If you can count how many scooters are in the system at any time (and how many belong to different providers) then you should be able to enforce your licencing regime. And if you know roughly where rides are going to / from and when, then that helps you integrate your different types of public transport - for example making sure that when the train arrives there are enough scooters there, or understanding how popular scooter ride paths interact with bike lanes, bus lanes, etc. Mobile phone cell size is generally a pretty good proxy for population density - modern micro-cell sectors can be pretty small, and 5G will make them even small in urban areas. (I work on this sort of stuff for a major engineering data science and asset management group in the UK).
  - malandrew 7y ago
    > which includes ability to find a distinct scooter I understand why a company needs to find a distinct schooter, but why does the city need the ability to find a distinct scooter?

morganherlocker 7y ago

This would not provide very much privacy protection at all. Almost all trips will be unique with this level of granularity, so it will be easy to de-anonymize. I do privacy research with this type of data and have found numerous sources that used aggregation schemes with similar levels of granularity. In those public datasets, I was able to identify trips moving between a high school and a local planned parenthood, for example. 100m is far smaller than the size of school campus and most buildings. To address privacy issues, data needs to be aggregated, with trip clusters with less than 5-10 trips dropped. Differential privacy strategies also exist, but dropping groups with low number of user contributions is the easiest solution to implement.