SKOS

Queries to explore a dataset

Even a schemaless one.

I recently worked on a project where we had a huge amount of RDF and no clue what was in there apart from what we saw by looking at random triples. I developed a few SPARQL queries to give us a better idea of the dataset’s content and structure and these queries are generic enough that I thought that they could be useful to other people.

In my last posting I described Carnegie Mellon University’s Index of Digital Humanities Conferences project, which makes over 60 years of Digital Humanities research abstracts and relevant metadata available on both the project’s website and as a file of zipped CSV that they update often. I also described how I developed scripts to convert all that CSV to some pretty nice RDF and made the scripts available on github. I finished with a promise to follow up by showing some of the…

I think that RDF has been very helpful in the field of Digital Humanities for two reasons: first, because so much of that work involves gaining insight from adding new data sources to a given collection, and second, because a large part of this data is metadata about manuscripts and other artifacts. RDF’s flexibility supports both of these very well, and several standard schemas and ontologies have matured in the Digital Humanities community to help coordinate the different data sets.

You probably don't need OWL

And if you do there's a simple way to prove it.

During the course of my recent blog posts What is RDF?, What is RDFS?, What else can I do with RDFS?, and Taxonomy management with SKOS, some readers wondered if I would do a “What is OWL?” followup. I recommended to one inquirer that he read pages 39-41 and 263 - 269 of Learning SPARQL; I think that provides a pretty good introduction to OWL’s history and how to do some of the set-based logic that was an important part of its original intent.

Taxonomy management with SKOS

Republishing an IBM developer works article.

In 2011, IBM developerWorks published an article that I wrote titled “Improve your taxonomy management using the W3C SKOS standard.” (They have always loved those “Get Better at This Thing” titles.) Several years later they took it (and a ton of other developerWorks content) down. I have republished it here as background for recent discussions about when OWL is appropriate to use and when it isn’t; more on that next month. I didn’t change anything but added a…

Converting JSON-LD schema.org RDF to other vocabularies

So that we can use tools designed around those vocabularies.

Last month I wrote about how we can treat the growing amount of JSON-LD in the world as RDF. By “treat” I mean “query it with SPARQL and use it with the wide choice of RDF application development tools out there”. While I did demonstrate that JSON-LD does just fine with URIs from outside of the schema.org vocabulary, the vast majority of JSON-LD out there uses schema.org.

Pulling SKOS prefLabel and altLabel values out of DBpedia

Or, using linked data to build a standards-compliant thesaurus with SPARQL.

When my TopQuadrant colleague Dean Allemang referred to the use of DBpedia as a controlled vocabulary, I said “Huh?” He helped me to realize that if you and I want to refer to the same person, place, or thing, but there’s a chance that we might use different names for it, DBpedia’s URI for it might make the best identifier for us to both use. For example, if you refer to the nineteenth-century American president and Civil War general Ulysses S. Grant and I refer to him as…