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Linked Digital Future - Un avenir numérique lié Successes and lessons learned in year one

As we wrap up a busy first phase of the Linked Digital Future initiative, we’d like to share a few successes and lessons learned with the performing arts community.

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Over the last year, CAPACOA and Culture Creates collaborated with the Bern University of Applied Sciences to develop a conceptual model for performing arts data. At the same time, Culture Creates was building the artsdata.ca knowledge graph, and RIDEAU was rolling out the Scène Pro information system. The former assembles data about performances; the latter gathers data about organizations, venues and performing arts productions. What if the two datasets were interoperable and could exchange data? We tried it out.

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Could Open Data Help Arts and Culture Listings? - snapshot from the blog post accompanying the report release

“Arts and culture listings are broken. Can open data help to make them better?” wondered Wales researchers from Nesta and The Satori Lab. In their recent discovery report, they concluded:

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We are half-way through the first full year of the Linked Digital Future initiative. Much has been accomplished already. And much has been learned.

In a spirit of openness and collaboration, we would like to share our complete Mid-Year Progress Report with the arts sector. The report offers an overview of what we’ve done and what we are currently up to. The report also includes several lessons learned, two of which I would like to share in this post.

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If you have been reading the Linked Digital Future report or any other literature about digital discoverability, you may have stumbled upon the term “knowledge graph” and wondered what on earth it can be.

Even experts disagree as to what a “knowledge graph” actually is. In simple terms, one could say that a knowledge graph is the combination of two things:

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Montreal, August 21, 2019 – “What shows can I see in Montreal tonight?” This is a rather straightforward question for a human being, but much more challenging one for AI-powered search and recommendation technologies. AI first needs to be taught what types of live performances exist, and it then requires quality structured data about actual live performances. A collective of performing arts organizations is about to do just that.

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