Computational Thinking, Cultural Analytics and Wikidata

I am very happy to be holding this workshop on knowledge graphs in art history at UC Berkeley's Visualization Lab for Digital Art History.

Today, art historical research is based on data. A computational and quantitative approach to the history of art requires volume of data, a variety of data and open data. Since we would like to embed each artwork in a cultural web of meaning, it would be best to have semantic data. However, what do the terms “open”, “semantic” and “data” actually mean?

In this workshop, we look at data sources for art history, data structures and levels of open data. We dive into several collections and find out how visualizing them helps us understand the history of art. At the center of our discussion is Linked Open Data. We particularly query Wikidata’s SPARQL endpoint. Thus, we are gaining data literacy through experience, discussing advantages and disadvantages of Wikidata and have a look at its alternatives.

We will use tools and data in the cloud. No programming skills required.