  Successfully managing analytics-based semantic relationships and their
provenance enables determinations of document importance and priority,
furthering capabilities for machine-based relevancy scoring operations.
Semantic technologies are well suited for modeling explicit and fully qualified
relationships but struggle with modeling relationships that are qualified in
nature, or resultant from applied analytics. Our work seeks to implement the
autonomous Directed Qualification of analytic-based relationships by pairing
the Prov-O Ontology (W3C Recommendation) with a relevancy ontology supporting
analytics terminology. This work results in the capability for any semantically
referenced document, concept, or named graph to be associated with the results
of applied analytics as Direct Qualification (DQ) modeled relational nodes.
This new capability will enable role, identity, or any other content-based
measures of relevancy and analytics-based metrics for semantically described
documents.
