  The Simple Knowledge Organization System (SKOS) is a standard model for
controlled vocabularies on the Web. However, SKOS vocabularies often differ in
terms of quality, which reduces their applicability across system boundaries.
Here we investigate how we can support taxonomists in improving SKOS
vocabularies by pointing out quality issues that go beyond the integrity
constraints defined in the SKOS specification. We identified potential
quantifiable quality issues and formalized them into computable quality
checking functions that can find affected resources in a given SKOS vocabulary.
We implemented these functions in the qSKOS quality assessment tool, analyzed
15 existing vocabularies, and found possible quality issues in all of them.
