Nice post! As a nuance, SKOS doesn't declare skos:broader as transitive so as to be robust to "dirty" thesauri. Instead they introduced a super-property (skos:broaderTransitive) for doing the inference automatically: https://www.w3.org/TR/skos-primer/#sectransitivebroader .
But for good thesauri, it is usually fair to think of skos:broader as transitive.
Hey there. Masterful flow here. I'm a bit jealy of your finding a new voice for these ageless practices. We all need to hear it to breath life back into old science.
Is this semantics or logic? If I don't know that 'bridge' can be a game or a structure, then narrower instances. like 'contract bridge' and 'suspension bridge' would fall under the same broader concept.
"For example, a SKOS‐aware reasoner can automatically infer that if Concept A is a skos:broader of Concept B, and Concept B is a skos:broader of Concept C, then Concept A is also a broader concept of Concept C. This kind of lightweight inferencing accelerates symbolic rule engines, enabling efficient query answering and classification, over a large thesauri."
Both. Ontologies introduce logical reasoning. Ontologies are semantic. Therefore ontologies are logical, semantic reasoning models. If you want to differentiate a game from a structure in SKOS, you add Bridge (Structure) and Bridge (Game) as a simple disambiguation setting. Simple parentheticals to differentiate.
"a SKOS thesaurus will deliver immense value, with or without AI. And with SKOS, you have built a knowledge graph, or what I like to call “knowledge graph lite”."
Great perspective. This might have some parallels in the structured data / BI world. Thanks!
Just what I needed today - was deep diving with someone on ontologies! Thank you! This part of your post, reflecting on the persisting importance of ontology : "Emerging AI research is discovering that symbolic AI is needed to drive accurate reliable AI results and even more critically, to bolster AI’s natural language conversational elements" - any recent readings you can recommend on that direction? That was a big and interesting statement in itself!
Nice post! As a nuance, SKOS doesn't declare skos:broader as transitive so as to be robust to "dirty" thesauri. Instead they introduced a super-property (skos:broaderTransitive) for doing the inference automatically: https://www.w3.org/TR/skos-primer/#sectransitivebroader .
But for good thesauri, it is usually fair to think of skos:broader as transitive.
Great add here. Thank you!
Thank you for that gem!
Hey there. Masterful flow here. I'm a bit jealy of your finding a new voice for these ageless practices. We all need to hear it to breath life back into old science.
Oh wow, thank you. This was a really hard one to write. I appreciate
Is this semantics or logic? If I don't know that 'bridge' can be a game or a structure, then narrower instances. like 'contract bridge' and 'suspension bridge' would fall under the same broader concept.
"For example, a SKOS‐aware reasoner can automatically infer that if Concept A is a skos:broader of Concept B, and Concept B is a skos:broader of Concept C, then Concept A is also a broader concept of Concept C. This kind of lightweight inferencing accelerates symbolic rule engines, enabling efficient query answering and classification, over a large thesauri."
Both. Ontologies introduce logical reasoning. Ontologies are semantic. Therefore ontologies are logical, semantic reasoning models. If you want to differentiate a game from a structure in SKOS, you add Bridge (Structure) and Bridge (Game) as a simple disambiguation setting. Simple parentheticals to differentiate.
See :
ANSI Z39.19: https://www.niso.org/publications/ansiniso-z3919-2005-r2010
ISO 25964: https://www.niso.org/schemas/iso25964
"a SKOS thesaurus will deliver immense value, with or without AI. And with SKOS, you have built a knowledge graph, or what I like to call “knowledge graph lite”."
Great perspective. This might have some parallels in the structured data / BI world. Thanks!
Immensely valuable for BI. Great observation, Zane!
Just what I needed today - was deep diving with someone on ontologies! Thank you! This part of your post, reflecting on the persisting importance of ontology : "Emerging AI research is discovering that symbolic AI is needed to drive accurate reliable AI results and even more critically, to bolster AI’s natural language conversational elements" - any recent readings you can recommend on that direction? That was a big and interesting statement in itself!
Hi Michael, there’s tons of research out there. I would read Gary Marcus’s paper linked in my article.
This paper is a great, comprehensive literature from 2024, about neuro-symbolic and sub-symbolic AI.
https://arxiv.org/abs/2501.05435