"After carrying out a subdivision of big data, the data that are to become “commons data” must then to a large extent be anonymized. Anonymization means that (a) the data are no longer private or personal and therefore constitute socialized data, and (b) the data are to a certain degree protected by the anonymization process, i.e., third parties should be prevented by regulation from misusing them; commercial and government bodies should be, for instance, prevented from using them for profiling or surveillance purposes.
The challenge to create regulations for the data protection issue is great: After all computing power is such today that anonymization is easily circumvented by cross-referencing many different datasets. Anonymization is held out as a solution, but a clever algorithm can fairly precisely identify an individual based on anonymous data. Here is a simplified example: One could, feasibly, triangulate an individual from (a) anonymized Uber user data (frequency of travelling to one location, must be their home); (b) anonymized Amazon data (shipped to the same postal code); and (c) a variety of invisible datamarks like type of computer, browser, etc.
According to the current state of the art, in addition to the anonymization of “commons data” it is also possible to anonymize and/or encrypt personal data. The anonymous communication provider Tor, for instance, enables users to visit a website, without their generating data which would permit a third party to establish a relationship between the individual and his or her access to the website. Also, the content of any personal digital communication may be encrypted so that only the sender and the recipient can read it. Some social networks additionally use technology to ensure that the personal data an individual has published are only shared with the individual’s personal contacts." (https://berlinergazette.de/big-data-in-our-hands/?p=20)