Speaker
Description
The Cell Key Method (CKM) is commonly used by statistics agencies to release tabular data. This paper compares the utility of a new open-source synthetic data tool, SynDiffix, with CKM for very fine-grained geographic data. SynDiffix is designed to have strong anonymity even when used by non-experts, and aims for high accuracy while maintaining strong anonymity. We compare the utility of SynDiffix and CKM for reported income data geocoded to 100x100m grid resolution. We show that, at this resolution, CKM is substantially more accurate than SynDiffix. On the other hand, we find that SynDiffix achieves comparable utility for larger geographic areas. Its flexibility, robustness, and ease-of-use make it more suitable for use cases where end-users can select data features on demand.