Hi,
Has anyone tried/succeeded importing the LoB vocabulary (https://lob.is.ed.ac.uk/) into Omeka-S v4.1.1?
I tried the turtle file that’s available as download, but I keep getting the “No classes or properties found”-error.
Thanks for any help,
Vincent
LoB is a thesaurus that contains SKOS concepts. Omeka expects vocabularies that contain RDF classes and properties.
Ah, right, is there a way to convert the LoB thesaurus, or do I have to rebuild it (or the parts of it which I need) in order to use it in Omeka-S?
It rather depends what you are trying to do. Can you say a bit more about how you are expecting to use it?
The “Vocabularies” bit of Omeka is where you create and maintain the properties (fields, if you prefer) that items can have. For example, a rare book vocabulary might have properties for “Binding”, “Paper type”, “Provenance” etc. It is not the same as a Controlled Vocabulary, (which might be a Thesaurus) which sets out what values the properties can take.
The Language of Bindings Thesaurus is a controlled vocabulary. As such you might want take a look at the Custom Vocab module or the Taxonomy module which offer two different approaches to controlled vocabularies in Omeka.
They serve different purposes. LoB contains concepts used to describe resources. Omeka S imports properties used to describe relationships between resources. For example, let’s deconstruct this sentence:
"This book" "is format" "paper pulp"
“This book” is the object resource. “Is format” is the predicate. “Paper pulp” is the subject resource (in this case a literal string). The Dublin Core vocabulary provides “is format” as a property. LoB provides “paper pulp” as a concept. There’s no way to convert concepts into properties.
LoB is more in line with the ValueSuggest module, though it does not include a LoB suggester.
Thank you, this - combined with Jim’s reply below - makes things clearer me.
Thank you. This - together with Matthew’s information above - clarifies things for me.
So I guess, when describing bookbindings, I better first look for properties/fields of existing ontologies and when I can’t find one for a specific aspect of something I want to describe, I can turn to creating a custum vocab (if possible based on LoB info).