  Here we understand 'intelligence' as referring to items of knowledge
collected for the sake of assessing and maintaining national security. The
intelligence community (IC) of the United States (US) is a community of
organizations that collaborate in collecting and processing intelligence for
the US. The IC relies on human-machine-based analytic strategies that 1) access
and integrate vast amounts of information from disparate sources, 2)
continuously process this information, so that, 3) a maximally comprehensive
understanding of world actors and their behaviors can be developed and updated.
Herein we describe an approach to utilizing outcomes-based learning (OBL) to
support these efforts that is based on an ontology of the cognitive processes
performed by intelligence analysts. Of particular importance to the Cognitive
Process Ontology is the class Representation that is Warranted. Such a
representation is descriptive in nature and deserving of trust in its
veridicality. The latter is because a Representation that is Warranted is
always produced by a process that was vetted (or successfully designed) to
reliably produce veridical representations. As such, Representations that are
Warranted are what in other contexts we might refer to as 'items of knowledge'.
