MaskMyPy: python tools for performing and analyzing geographic masks.

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
David Swanlund, Nadine Schuurman
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引用次数: 0

Abstract

Background: Geographic masking is an important but under-utilized technique for protecting and disseminating sensitive geospatial health data. Geographic masks work by displacing static point locations such that the people those locations describe cannot be identified, while at the same time preserving important spatial patterns for analysis. Unfortunately, there is a lack of available tooling surrounding geographic masks which we believe creates an unnecessary barrier towards the adoption of these techniques. As such, this article presents a set of tools for performing, evaluating, and developing geographic masks, called MaskMyPy.

Results: MaskMyPy is an open-source Python package that includes functions for performing geographic masks, including donut, street, location swapping, and Voronoi masks. It also includes a range of tools for evaluating the results of these masks, both with regard to privacy and information loss. Finally, it includes a special class called the 'Atlas' that aims to dramatically streamline mask execution and evaluation. We conducted a short case study to illustrate the power of MaskMyPy in geographic masking research, and in doing so showed that mask performance can range widely due solely to randomization. As such, we recommend that masking researchers test their masks repeatedly across a variety of test datasets.

Conclusion: MaskMyPy makes it easy to apply a variety of geographic masks to a set of sensitive points and then measure which mask provided the most privacy while suffering the least information loss. We believe this style of tooling is important to not only make geographic masks accessible to non-experts, but to enable expert users to better interrogate the masks they develop, and in doing so drive the geographic masking discipline forward.

MaskMyPy:用于执行和分析地理掩码的python工具。
背景:地理掩蔽是保护和传播敏感地理空间卫生数据的一种重要但未得到充分利用的技术。地理掩模的工作原理是取代静态的点位置,使这些位置所描述的人无法识别,同时保留重要的空间模式以供分析。不幸的是,缺乏可用的地理掩码工具,我们认为这给采用这些技术造成了不必要的障碍。因此,本文提供了一组用于执行、评估和开发地理掩码的工具,称为MaskMyPy。结果:MaskMyPy是一个开源Python包,包含执行地理掩码的函数,包括甜甜圈、街道、位置交换和Voronoi掩码。它还包括一系列工具,用于评估这些掩码在隐私和信息丢失方面的结果。最后,它包括一个名为“Atlas”的特殊类,旨在显着简化掩模执行和评估。我们进行了一个简短的案例研究,以说明MaskMyPy在地理掩蔽研究中的作用,并在这样做的过程中表明,仅仅由于随机化,掩蔽性能的范围可能很大。因此,我们建议口罩研究人员在各种测试数据集中反复测试他们的口罩。结论:MaskMyPy可以很容易地对一组敏感点应用各种地理掩码,然后测量出哪些掩码提供了最多的隐私,而遭受的信息损失最少。我们相信这种风格的工具非常重要,不仅可以让非专家也可以使用地理掩码,还可以让专家用户更好地询问他们开发的掩码,并以此推动地理掩码学科向前发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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