Empowering Open Data Sharing for Social Good: A Privacy-Aware Approach

Tânia Carvalho, Luís Antunes, Cristina Costa, Nuno Moniz
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Abstract

The Covid-19 pandemic has affected the world at multiple levels. Data sharing was pivotal for advancing research to understand the underlying causes and implement effective containment strategies. In response, many countries have promoted the availability of daily cases to support research initiatives, fostering collaboration between organisations and making such data available to the public through open data platforms. Despite the several advantages of data sharing, one of the major concerns before releasing health data is its impact on individuals' privacy. Such a sharing process should be based on state-of-the-art methods in Data Protection by Design and by Default. In this paper, we use a data set related to Covid-19 cases in the second largest hospital in Portugal to show how it is feasible to ensure data privacy while improving the quality and maintaining the utility of the data. Our goal is to demonstrate how knowledge exchange in multidisciplinary teams of healthcare practitioners, data privacy, and data science experts is crucial to co-developing strategies that ensure high utility of de-identified data.
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增强开放数据共享的社会效益:注重隐私的方法
Covid-19 大流行在多个层面对世界造成了影响。数据共享对于推动研究以了解根本原因和实施有效的遏制战略至关重要。为此,许多国家推动提供每日病例以支持研究计划,促进组织间的合作,并通过开放数据平台向公众提供此类数据。尽管数据共享具有多种优势,但在发布健康数据之前,人们主要关注的问题之一是其对个人隐私的影响。这种共享过程应基于设计和默认数据保护的最新方法。在本文中,我们使用了葡萄牙第二大医院 Covid-19 病例的相关数据集,以展示如何在提高数据质量和保持数据效用的同时确保数据隐私。我们的目标是展示由医疗从业人员、数据隐私和数据科学专家组成的多学科团队中的知识交流对于制定确保去标识化数据高度实用性的策略是多么重要。
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