论文标题
Google Covid-19社区移动性报告：匿名过程描述（版本1.1）
Google COVID-19 Community Mobility Reports: Anonymization Process Description (version 1.1)
论文作者
论文摘要
This document describes the aggregation and anonymization process applied to the initial version of Google COVID-19 Community Mobility Reports (published at http://google.com/covid19/mobility on April 2, 2020), a publicly available resource intended to help public health authorities understand what has changed in response to work-from-home, shelter-in-place, and other recommended policies aimed at flattening the curve of the COVID-19 大流行。我们的匿名过程旨在确保没有个人数据（包括个人的位置，移动或联系人）可以从结果指标中得出。 该过程的高级描述如下：我们首先从选择进入位置历史记录的Google用户的数据中生成一组匿名指标。然后，我们根据匿名指标的历史部分计算这些指标的百分比变化。然后，我们丢弃一个不符合我们标准的子集以获得统计可靠性，并以将结果与私人基线进行比较的格式公开发布。
This document describes the aggregation and anonymization process applied to the initial version of Google COVID-19 Community Mobility Reports (published at http://google.com/covid19/mobility on April 2, 2020), a publicly available resource intended to help public health authorities understand what has changed in response to work-from-home, shelter-in-place, and other recommended policies aimed at flattening the curve of the COVID-19 pandemic. Our anonymization process is designed to ensure that no personal data, including an individual's location, movement, or contacts, can be derived from the resulting metrics. The high-level description of the procedure is as follows: we first generate a set of anonymized metrics from the data of Google users who opted in to Location History. Then, we compute percentage changes of these metrics from a baseline based on the historical part of the anonymized metrics. We then discard a subset which does not meet our bar for statistical reliability, and release the rest publicly in a format that compares the result to the private baseline.
