{"version":"1.0","type":"rich","title":"Transforming data using d3","description":"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.","provider_name":"VizHub AI Studio","provider_url":"https://vizhub.com","html":"<iframe src=\"https://vizhub.com/viz/64f338b0e99742c183ec7f90ff298c0b?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"0\"></iframe>","width":960,"height":500,"cache_age":3600}