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A context sensitive approach to anonymizing public participation GIS data: From development to the assessment of anonymization effects on data quality

机译：匿名匿名公众参与GIS数据的语境敏感方法：从开发到评估对数据质量的匿名效果

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摘要

Use of Public Participation Geographic Information System (PPGIS) for data collection has been significantly growing over the past few years in different areas of research and practice. With the growing amount of data, there is little doubt that a potentially wider community can benefit from open access to them. Additionally, open data add to the transparency of research and can be considered as an essential feature of science. However, data anonymization is a complex task and the unique characteristics of PPGIS add to this complexity. PPGIS data often include personal spatial and non-spatial information, which essentially require different approaches for anonymization. In this study, we first identify different privacy concerns and then develop a PPGIS data anonymization strategy to overcome them for an open PPGIS data. Specifically, this article introduces a context-sensitive spatial anonymization method to protect individual home locations while maintaining their spatial resolution for mapping purposes. Furthermore, this study empirically evaluates the effects of data anonymization on PPGIS data quality. The results indicate that a satisfactory level of anonymization can be reached using this approach. Moreover, the assessment results indicate that the environmental and home range measurements as well as their intercorrelations are not significantly biased by the anonymization. However, necessary analytical measures such as use of larger spatial units is recommendable when anonymized data is used. In this study, European data protection regulations were used as the legal guidelines. However, adaptation of methods employed in this study may be also relevant to other countries where comparable regulations exist. Although specifically targeted at PPGIS data, what is discussed in this paper can be applicable to other similar spatial datasets as well.
机译：在过去几年中，使用公共参与地理信息系统（PPGIS）在不同的研究和实践领域，在过去几年中受到显着增长。随着数据的越来越多的数据，毫无疑问，潜在更广泛的社区可以从对他们的开放访问中受益。此外，开放数据增加了研究的透明度，可以被视为科学的重要特征。但是，数据匿名化是一个复杂的任务，PPGI的唯一特征是添加到此复杂性。 PPGIS数据通常包括个人空间和非空间信息，其基本上需要不同的方法来匿名化。在本研究中，我们首先确定不同的隐私问题，然后开发PPGIS数据匿名策略，以克服它们的开放PPGIS数据。具体地，本文介绍了一种上下文敏感的空间匿名化方法，用于保护个别家庭位置，同时保持其空间分辨率以进行映射目的。此外，本研究经验验证了数据匿名化对PPGIS数据质量的影响。结果表明，可以使用这种方法来达到令人满意的匿名水平。此外，评估结果表明，环境和家庭范围测量以及其同期并不明显被匿名化偏置。但是，当使用匿名数据时，必要的分析措施如使用较大的空间单元。在本研究中，欧洲数据保护法规被用作法律指导方针。然而，本研究中所采用的方法的适应也可能与存在可比法规的其他国家相关。虽然专门针对PPGIS数据，但本文中讨论的内容也可以应用于其他类似的空间数据集。

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