I'm involved in a project[0] that has an aim to provide better data integration by using OBOFoundry ontologies, but it's been a challenge in practice to merge the software with the ontologies in a coherent way.
While we at SIB are more towards the RDF/SPARQL part of the spectrum (https://edu.sib.swiss/course/view.php?id=440). We do use OWL and obofoundry projects like Uberon and GO. For UniProt I took a lot of pain to make sure it is really compatible. We did the same for Rhea and ChEBI. This has paid of handsomely in new query capabilities.
I've come across things a simple as "I wrote a Perl script that does that, but it uses KEGG not GO terms" for their reasoning. That, or – if they're okay with using gene ontology – we have to also use the other system in parallel. And then the results becomes a discussion of how the two different annotation systems display the results.
Life science could use a benevolent dictator.
If there's going to be one it has to be the NIH. Since they've been investing a lot in this field.
The problem is culture. Principal investigators are notoriously stubborn about how they do things, and that includes what they call things. Manufacturers and supply companies also don’t see much benefit to standardizing around this, and of course realize the large downside (alienating the aforementioned PIs).
What would help this would be the introduction of OWL into major software suites, primarily LIMS and ELN packages, and include tools for aligning terminology and concepts with OWL.