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Separate Ontology for Examples #8
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That makes sense. I agree with you in the sense that we should keep the essential instances On Tue, Mar 3, 2015 at 12:50 PM, Michael Cotterell <[email protected]
Mustafa Veysi Nural |
@mvnural, I've set this issue to accepted. However, before we implement as explained in my original post, I'd like to suggest the following to make things even easier. We should should have an ontology for each example dataset. For each dataset, we could have multiple model examples. My reasoning for having multiple ontologies for the examples is that it might get confusing if variable names are shared between datasets. What do you think? |
I'm not sure. It might be both Yes and No. It's yes because the only reason we have it this way is for convenience. We It's no because think of the case where we have field headers of a dataset On Tue, Mar 3, 2015 at 8:22 PM, Michael Cotterell [email protected]
Mustafa Veysi Nural |
I thought more about this and decided that having an ontology for each dataset should be fine. Even if same variable is used across datasets (e.g., mpg), they are only conceptually related but different entities. So please ignore my previous concern. |
I think it would be a good idea for us to have analytics.owl not contain any individuals from the examples. Instead, create analytics-examples.owl which imports analytics.owl and include the examples there. This way, the size of the main ontology is minimized, which means our code for classifying should run faster.
Of course, we find that some individuals are always needed (as might be the case with some of the functions or distributions), then we can of course include them analytics.owl.
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