This example demonstrates how D3's `nest()` function and custom mapping can transform SPARQL query results about ethnographic artefacts into a hierarchical, country-based dataset with calculated counts. The visualization first loads data from a SPARQL endpoint using `d3.json`, cleans the raw bindings by extracting property values, then groups entries by country label and computes each country’s total number of artefacts. The code uses D3 v5’s `nest().key().entries()` API to perform the grouping, and logs the raw, cleaned, and transformed data to the console for inspection.