Introduction to Wikidata
summary
Demo shows running SPARQL‑style queries (referred to as Sparkle) from Jupyter notebooks using a SPARQL wrapper or kernel, pandas and IPython display to pull images and identifiers — for example a Chinchilla Cafe bands query that returns band names, WikiData IDs and images. Session describes importing clinical datasets such as a clinicaltrials.gov import, notes WikiData runs on ~13 servers with billions of triples and 15+ million items, and emphasizes which queries succeed, time out, or surface surprising gaps.
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chapters (12)
- 0:00Wikidata introduction
- 1:06Wikidata vs Wikipedia
- 8:32Wikipedia statistics
- 13:48Wikidata updates
- 20:04Open Street Map and Wikidata collaboration
- 27:10SPARQL in Wikidata
- 33:13Bias in Wikidata
- 42:49Data exchange politics
- 52:18Clinical trials import
- 1:00:03Wikimedia funding
- 1:04:55Article-item links
- 1:08:26Query limits and properties
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