After I understood how Wikidata worked and had begun contributing to it, I thought it was the solution to everything. It made complete sense — a federated, linked, semantic database of everything. What else would anyone need? It would be the hammer for every nail.

Excited, I began showing it to my friends and family. With each demo, I realized that Wikidata is a difficult hammer to use. A friend pointed out the obvious, “Interesting… but how will people use it? No one is going to learn SPARQL”. Even changing the name of the painter in the “show me paintings of Amrita Sher-Gil query” isn’t trivial. And working with Wikidata’s Q-id isn’t straightforward either.

The only other way to query this immense dataset is to wait for the big tech companies to eat up all this CC-O data. Siri, Alexa, and Google Assistant will become smarter with it, but they’ll remain a closed ecosystem that often harm the projects they benefit from. On the other hand however, the Google Art Project has helped Commons. Still, it too remains a system of closed collection and curation, with no room for correction or contribution.

While we wait for an open source Virtual Interactive Kinetic Intelligence (VIKI), I wonder what an open virtual museum would be like — a Wikiseum! A VR experience on the open web using open data. Paintings from museums across the world, and a museum guide who speaks your language.

All this is technologically already possible — Wikidata has numerous statements on paintings and museums which is only going to increase with structured data on Commons. Commons itself has scans of many paintings, and Wikipedia has detailed information about paintings, their artists, and the museums they are in.

All that is left to do is some plumbing and a UI.