“Which Canadian federal, provincial, and municipal open datasets are known to have data quality, normalization, or identifier problems that prevent joining them, and what specific defects do journalists or researchers cite?”
This is a curated evidence matrix of 24 documented cases — 8 federal, 8 provincial, 8 municipal — selected as the strongest documented interoperability failures found in the scan, not a census of all defective Canadian datasets. Evidence comes from 13 independent source hosts; one entity-resolution source backs 7 of the 24 cases and the Investigative Journalism Foundation backs 5, and shared sourcing is marked throughout. In 11 of the 24 cases the critic calls the join outright impossible; the rest are possible but biased, incomplete, or manually normalized.
| Level | Dataset / case | Defect family | Exact defect | Consequence | Source |
|---|
Evidence matrix of 24 curated cases of documented join, identifier, and data-quality failures in Canadian open datasets (8 federal, 8 provincial, 8 municipal), drawn from 13 independent source hosts cited by journalists and researchers; the largest host backs 7 cases. Each row is one dataset/case with its exact cited defect and consequence; severity marks whether the critic calls the join impossible or merely degraded. Defect families are an editorial grouping of the cited defects. Quantitative details are quoted where the source gives them; long defect texts are truncated in the table and shown in full via the matrix. Compiled 2026; this is a curated shortlist from an evidence scan, not a census.