Local law enforcement jumps on the Big Data bandwagon: Automated license plate recognition systems, information privacy, and access to government information

This paper presents findings from an exploratory empirical analysis of two automated license plate recognition (ALPR) databases, consisting of more than 1.7 million license plate scans in Seattle, Washington. I present tabulated summary data, geo-spatial visualizations, and offer a theoretical and legal analysis of the tensions between privacy and access to information implicated by the public disclosure of surveillance databases. One recently popular legal response (in the USA and Canada), limiting ALPR data retention, protects the privacy of innocent individuals whose plates happen to be scanned, but it also limits the ability of the public to conduct oversight.