(Obviously SNOMED CT is difficult for me to work with as it is licensed
and not available directly in RDF, at least last time I looked - you
have to produce it locally- It was about 5M triples.
On 22/09/2021 03:09, Brandon Sara wrote:
We need the inference so that we can know equivalence between classes and subclass relationships
(eg "type 2 diabetes" is still "diabetes" because it's is a subclass of
diabetes).
Which is only rdfs;subClassOf? (it in ICD-10 CM)
Another dataset that I've never been able to get to load with any inference
enabled is SNOMED CT.
SNOMED produce a version with the transitive closure already calculated.
Even when removing all of the owl inference that they have in their dataset and
pre-calculating the direct subclass relationships, not even the transitive
reasoner will load the dataset
(overlap with discussion with Ryan).
The general OWL reasoners have an axiomatic rule that touches the whole
dataset. I doubt you need axiomatic inferences.
And if precalculated transitive closure, do you need an inference engine
at runtime at all?
(riot --rdfs will expand sublcass and subproperty ahead of time)
(without modification at runtime) once the first query is submitted after
startup of Fuseki. Granted it's it significantly larger than ICD-10 CM. But
still, not being able to load it with even pre-calculated direct subclass
relationships is a huge deal breaker. Not to mention the fact that the real
power of that dataset comes when the owl inference built into it can actually
be used. With it, inference on patient data can reveal potential diagnoses that
would not be inferred without and owl reasoning.
Which reasoner? IIRC SnomedCT uses various OWL features.
The default RDFS reasoner does not include the "rdf4" rule which is a
whole-dataset rule.
A ruleset tuned to needs may work better.
Andy
