Empowering open data sharing for social good: a privacy-aware approach

Area of Science:

• Health Informatics
• Data Privacy
• Epidemiology

Background:

• The Covid-19 pandemic highlighted the critical need for data sharing to advance research and inform public health strategies.
• Open data platforms facilitated access to daily case data, promoting collaboration and public access.
• Balancing data sharing benefits with individual privacy concerns is a significant challenge in health research.

Purpose of the Study:

• To demonstrate the feasibility of ensuring data privacy in health datasets.
• To show how data quality and utility can be maintained alongside privacy protection.
• To emphasize the importance of multidisciplinary collaboration in developing data sharing strategies.

Main Methods:

• Utilized a Covid-19 dataset from a major Portuguese hospital.
• Applied state-of-the-art methods in Data Protection by Design and by Default.
• Focused on co-developing strategies through collaboration between healthcare, data privacy, and data science experts.

Main Results:

• Successfully demonstrated that health data can be de-identified while preserving its quality and utility.
• Showcased a practical approach to privacy-preserving data sharing for Covid-19 research.
• Validated the effectiveness of multidisciplinary teams in creating robust data protection solutions.

Conclusions:

• Knowledge exchange among healthcare practitioners, data privacy experts, and data scientists is crucial for effective de-identified data strategies.
• Implementing Data Protection by Design and by Default principles is essential for ethical health data sharing.
• Privacy-preserving data sharing enhances research capabilities without compromising individual confidentiality.