> When organizations claim to have "anonymized" a data set, what exactly to that mean? For "organizations" in general? It means approximately nothing, or if y

> When organizations claim to have "anonymized" a data set, what exactly to that mean? For "organizations" in general? It means approximately nothing, or if you're feeling particularly generous, it means "we probably remembered to drop the column containing your social security number before publishing this data... this time". You're asking exact specifics of a vague and broad category. There are some legal standards, information theory, and non-legal organization standards that might being met in some cases - involving adding noise or removing data / making it sparse. https://en.wikipedia.org/wiki/Data_re-identification https://en.wikipedia.org/wiki/Data_re-identification goes into all the ways that it can go wrong despite the best of intentions. My basic take on this all is: data "always" gets more identifying, not less. Two datasets that were successfully anonymized individually can still be correlated to de-anonymize some or all of the data when combined. Even organizations applying information theory with the best of intentions and proper diligence will eventually make a mistake.