一个功能测试解决方案，以应对开放公交支付系统交易数据的挑战
A Functioning Beta Solution to the Challenge of Opening Transit Payment System Transaction Data
摘要：
基于智能卡的公共交通票价支付系统的部署为政府提供了创造有价值的衍生数据产品的机会。像Urban Engines这样的公司已经展示了为来自过境票价交易的数据增值的能力。公共部门面临的挑战是，为了社会的利益，通过以保护客户隐私的方式提供有用的票价交易数据来利用私营部门的利益。这一挑战在加利福尼亚州尤为严峻，因为隐私法使得以支持公共利益的方式共享数据变得困难。本文介绍了大都会运输委员会（MTC）提出的解决方案的问题。MTC为旧金山湾区运营Clipper（r）过境票价支付系统。在努力分享有用的数据，保护客户的隐私，MTC开发了一个匿名方案，这是本文的主题。我们从Data for Good Exchange社区寻求对我们方法的反馈，询问：在寻求客户隐私和可用性之间的平衡时，该计划是否在任何一个方向上都走得太远？我们是否应该采取不同的匿名方法？
英文摘要：
The deployment of smart-card-based public transit fare payment systems provides government the opportunity to create a valuable derivative data product. Companies such as Urban Engines have demonstrated an ability to add value to the data derived from transit fare transactions. The challenge for the public sector is to, for the societal good, leverage private sector interest by giving access to useful fare transaction data in a manner that protects customer privacy. This challenge is particularly acute in California, where privacy laws make sharing data in a manner that supports the public interest difficult. This paper presents the Metropolitan Transportation Commission's (MTC's) proposed solution to the problem. MTC operates the Clipper(r) transit fare payment system for the San Francisco Bay Area. In an effort to share usable data that protects customer privacy, MTC developed an anonymizing scheme that is the subject of the present paper. We seek feedback on our approach from the Data for Good Exchange community, asking: in seeking a balance between customer privacy and usability, does the scheme go too far in either direction? And, should we take a different anonymizing approach?
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
