What I wondered about that data set is, if two people living/working at two locations, consistently take taxis to meet at various other locations at the same times, could that pattern be identified in the data?
That is, are there locations A and B such that there are matching trips to locations M1,M2,... at times T1,T2,... i.e. (A,M1,T1),(B,M1,T1),(A,M2,T2),(B,M2,T2) and perhaps reverse trips (M1,A,T1+x) etc?
Further classification of M* -- hotels, for example -- could classify the nature of the meetings. You might be able to identify the addresses of people having affairs, or other deliberately secret rendezvous.
This would be relatively difficult for Manhattan, some parts of the outer boroughs though are a different matter.
I was concerned when this first hit HN because I have a friend that lives in a fairly sparsely part of town and his (now ex) girl friend has a possessive ex-husband that doesn't like her seeing other men. He isn't going to be able to make sense of the data himself, but if someone weaponizes it the way you are talking about it could be a real problem for people with stalkers/psycho-exes.
I wonder if you could build a small, money generating business from answering exactly that. If you could get more recent data dumps at some interval, you could even provide an email alert system.
That is, are there locations A and B such that there are matching trips to locations M1,M2,... at times T1,T2,... i.e. (A,M1,T1),(B,M1,T1),(A,M2,T2),(B,M2,T2) and perhaps reverse trips (M1,A,T1+x) etc?
Further classification of M* -- hotels, for example -- could classify the nature of the meetings. You might be able to identify the addresses of people having affairs, or other deliberately secret rendezvous.