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This Web site explains a new, soon-to-be patented method which makes it possible to do something that would seem impossible -- to use a highly-detailed, GPS-derived track of an individual's movements without compromising that person's privacy.

The key to the method is to track each person for a limited period of time (e.g. 24 hours) and to blur his location selectively so that we can see exactly where he is when he is in crowded public places but only approximately where he is at other times. In this way, the method makes it impossible to identify the person from the track -- that person's anonymity is protected, and the track can be used without violating his privacy (assuming that he consented to being tracked).

These individual tracks are rich in detail. And analyzing collections of tracks is straightforward.

As a source of data on the movement of people, the anonymized tracks compare favorably with the data used by 'big data' approaches (e.g. PlaceIQ, SenseNetworks). To preserve individuals' privacy, those methods aggregate (i.e. lump together) the tracks of many people. Obviously, this aggregation involves a huge loss of detail. Big data seeks to compensate for the loss of detail by using massive quantities of data and very sophisticated mathematics. I wish them the best in that endeavor, but it would certainly seem simpler to anonymize individual tracks so that they can be analyzed directly.

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