Ontologies and structuring knowledge graphs, best practices

[e_Spirals]

Been playing with chatGPT a bunch and exploring it’s ability to create syntax for diagrams and it’s utilization of pre-existing knowledge graphs. This has led into a rabbit hole of ontologies and semantic structuring of data.
I’ve only been using Logseq as an outliner and have come to realize I could be adding other data elements to transform my notes db of outlines into a more powerful knowledge graph. My intention is to have my specialized knowledge graph in a “best practices” format that chatGPT can then access and use to answer domain specific queries.

I’ve been using Logseq for about 6mths just applying the concept of Atomic Habits and daily journaling. I’ve not used tags, nor queries, nor much of the functionality that is here and just discovered this forum.

Hope to contribute more once I become for agile with this powerful tool.
To all those whom been building here, props!

[alex0]

Have you thought about using the terms listed here https://schema.org/ ?

It’s the “vocabulary” that search engines understand when indexing the Web. Also, there is a script to export Logseq graphs as RDF that means interoperability with other related tools. It would me more than sane to adopt Schema.org from the beginning.

[e_Spirals]

This is useful bird’s eye view tyvm. My current high level markmap.