2020 was the "year of the Knowledge Graph". As I have pointed out, XBRL is a knowledge graph devised in 1999, long before Google came up with the term "knowledge graph" in 2012. Prolog, RDF, SQL, GQL are also all declarative approaches to representing knowledge graphs.
The take away from the article above is:
For knowledge graph technologies to have a broader impact, we shouldn’t be dogmatic about a term that was invented by Google’s product marketing department. We shouldn’t insist on adoption of standardized markup schemes or the creation of a centralized graph database because that didn’t work for the Semantic Web, and it won’t work for the corporate web.
If we instead listen to the problems information workers have, spend a day shadowing them in their jobs, and design solutions that integrate knowledge-tech in a lightweight way to automate tedium, then we have a shot at solving a larger set of problems, to benefit more of society.
Linked to the article above is this excellent article by some folks from Deloitte in Germany: Wisdom of Enterprise Knowledge Graphs. If you read nothing else, read the CONCLUSION of that document. But the entire document is worth reading.
Have a look at what you can do with a knowledge graph in this 3 minute YouTube video. They are using KgBase. Accountants (and others) can learn about knowledge graphs for free.
Remember, an XBRL-based digital financial report is a knowledge graph.
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What is Small Data (YouTube Video)
Generating Small Data can Solve Big Problems (TedTalk)