Which of the following is not part of privacy-preserving geospatial analytics?

• A. Differential privacy
• B. Data aggregation
• C. Access controls
• D. Publishing raw location data to external stakeholders

Answer: (D)

Protecting individuals’ location privacy while still gaining useful geospatial insights is the goal. Publishing raw location data to external stakeholders directly reveals exact places and movements, making it easy to identify people and expose sensitive patterns. That undermines privacy and isn’t part of privacy-preserving analytics.

In contrast, differential privacy adds carefully calibrated randomness to outputs so the impact of any single person’s data is hidden, preserving privacy while keeping results useful. Data aggregation groups data into summaries or larger areas, reducing precision and the risk of identifying individuals. Access controls restrict who can view or share data, preventing unauthorized access. These approaches collectively support privacy in geospatial analytics, whereas sharing raw data does not.