Analyzing, visualizing and improving Wikidata using the Wolfram Language
10-30, 15:00–15:55 (UTC), Room 1

Wikidata aims to provide an identifier and associated data for every concrete or abstract concept. This ambitious goal will facilitate many new use case, but also poses challenges in terms of data completeness and quality.
The Wolfram Language (WL) is an easy to learn programming language with built-in support for computation, visualisation, machine learning, access to databases and the semantic web and, last but not least, a dedicated Wikidata function.
In this talk I'll show some of the cool things you can do with Wikidata using the WL, including retrieval, querying, analysis, visualisation, comparison and curation of data.
Whether you are new to Wikidata or an experienced contributor, whether you know the WL or no programming at all, you'll learn something new.

Link to notes

What will the participants take away from this session?

Participants will learn how to retrieving data, query and visualize different kinds of data (numbers, dates, graphs, ...), learn some ticks for data cleanup and spotting possible mistakes either by working only on Wikidata's data or by comparison to built-in data or external data, all in the Wolfram Language (WL).
They'll also see how to work with dedicate functionality related to certain knowledge areas.
Finally, participants learn more about Wikidata's data model related to quantities and units, and some techniques for ensuring their high quality.