Harris Daniel R, Delcher Chris
Institute for Pharmaceutical Outcomes and Policy, College of Pharmacy, Center for Clinical and Translational Sciences, University of Kentucky, Lexington, KY USA.
Institute for Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Kentucky, Lexington, KY USA.
Proc IEEE Int Conf Big Data. 2019 Dec;2019:4067-4070. doi: 10.1109/bigdata47090.2019.9006234. Epub 2020 Feb 24.
Geocoding, the process of translating addresses to geographic coordinates, is a relatively straight-forward and well-studied process, but limitations due to privacy concerns may restrict usage of geographic data. The impact of these limitations are further compounded by the scale of the data, and in turn, also limits viable geocoding strategies. For example, healthcare data is protected by patient privacy laws in addition to possible institutional regulations that restrict external transmission and sharing of data. This results in the implementation of "in-house" geocoding solutions where data is processed behind an organization's firewall; quality assurance for these implementations is problematic because sensitive data cannot be used to externally validate results. In this paper, we present our software framework called bench4gis which benchmarks privacy-aware geocoding solutions by leveraging open big data as surrogate data for quality assurance; the scale of open big data sets for address data can ensure that results are geographically meaningful for the locale of the implementing institution.
地理编码，即将地址转换为地理坐标的过程，是一个相对简单且研究充分的过程，但由于隐私问题导致的限制可能会制约地理数据的使用。这些限制的影响因数据规模而进一步加剧，进而也限制了可行的地理编码策略。例如，医疗保健数据除了可能存在限制数据外部传输和共享的机构规定外，还受到患者隐私法的保护。这导致了“内部”地理编码解决方案的实施，即在组织的防火墙后处理数据；这些实施的质量保证存在问题，因为敏感数据不能用于外部验证结果。在本文中，我们展示了我们的软件框架bench4gis，它通过利用开放大数据作为替代数据进行质量保证，对标注重隐私的地理编码解决方案；用于地址数据的开放大数据集的规模可以确保结果在实施机构所在地区具有地理意义。
