Also as someone doing my own implementation at the moment, I expect that there is a big relational database backing the MELT store, just the graph aspect is functionally a big RAG interface on top of it acting as a search cache, not itself the data store.
Talk about what they built, not the business problem it solved and how it created value somewhere.
Agreed that centralizing identity is critical (which implies strong reconciliation systems, that can both do well on merges/splits/identity-shifts, but also need to enable backtracing to sources for each triple), but then I don't think it makes sense anymore to force ontology across all systems in the pipeline. As long as you give AI ability to do toolcalls/skills for each individual system and let it build up memory, then AI does much better job piecing together the actual practical ontology. You can give the observability AI to ask each system about it's state for the given piece of information and the AI should be free to make any toolcalls (e.g. call the specific system appropriately via CLI) it needs to gather the precise state.
I think human establishing the ontology gets in a way here, just let the AI poke the systems on its own via clean small interfaces.
In theory, at least.
Observability vendors have been beating the drum for 10+ years that there's so much untapped business value in operational data. Seems like we might be getting close to seeing how real that is.
Forgive the anthropomorphizing, it was necessary - "terms" has double meaning there, and each of us can understand that without an ontology - because we can access nuance. I can read schema, structure, and shape, and understand; but only one of those triggered some readers.
Anyway, the machines will choose terms which are most well-represented in the training data. This will normalize communication by chopping off the top-end where nuance lies. This is token-efficient.
Ontologies, in their implementation in the Linked Data ecosystem, do offer the ability to relate one understanding-system to another, but this is not token-efficient. I would love to see each domain, each business even, define their view of the world in the most expressive and culture matching owl representation, but I don't see it happening. "Shape" it is.
If the preference is for books, I can recommend "Semantic web for the working ontologist: effective modeling for linked data, RDFS, and OWL". https://search.worldcat.org/title/1193030282
If the preference is for papers, two papers from Deborah McGuinness et al, from early 2000s are still my favorites:
- "Ontology development 101: A guide to creating your first ontology": https://scholar.google.com/citations?view_op=view_citation&h...
- "Ontologies come of age": https://scholar.google.com/citations?view_op=view_citation&h...
- https://en.wikipedia.org/wiki/Category:Technical_communicati...
- https://en.wikipedia.org/wiki/Category:Knowledge_representat...
- https://en.wikipedia.org/wiki/Category:Information_science
It really is a idea-rabbit hole though, and kind of hard to stop yourself from wanting to create N new projects based on every new idea and perspective you come across.
relevant hn
https://news.ycombinator.com/item?id=49878857 - A Staff Engineer's Guide to Inventing Work
Tech industry is overstaffed to the gills . No one really knows how to create value for customers( only for themselves through these overegineered slop for career advancement) . Tech jobs are really sad place to be now.
Er... nope.
In the limited context of OWL and RDF, that's what an ontology is. It has a much larger meaning outside of that context. As M-W puts it, ontology is "the branch of metaphysics concerned with the nature and relations of being."
Projected into computer science, an ontology is a formal model of concepts in a domain, their properties and relationships, along with axioms or constraints that apply to those concepts.
The "triple" described in the quote is an implementation detail, how a particular formalism (OWL and RDF) chooses to represent a rather pale shadow of what an ontology is conceptually.