  Knowledge graphs and ontologies are becoming increasingly vital as they align
with the FAIR Guiding Principles (Findable, Accessible, Interoperable,
Reusable). We address eleven challenges that may impede the full realization of
the potential of FAIR knowledge graphs, as conventional solutions are perceived
to be overly complex and lacking in cognitive interoperability. We extend the
concept of "semantic units" as a conceptual solution by adding further
subcategories. Semantic units structure a knowledge graph into identifiable and
semantically meaningful subgraphs, with each subgraph being represented by a
resource that instantiates a semantic unit class. We introduce some-instance,
most-instances, every-instance, and all-instances resources as new types of
representational entities in addition to named-individual, class, and property
resources. We combine these new resource types with the concept of semantic
units and introduce new subcategories of statement units and semantically
meaningful collections of statement units (i.e., compound units) that provide
solutions to the eleven challenges. These include, for instance, schemes for
modelling assertional, contingent, prototypical, and universal statements,
including class axioms, as well as absence statements, negations, and
cardinality restrictions. The schemes are alternatives to existing OWL-based
modelling schemes, and we provide corresponding representations for them that
do not involve blank nodes. With question units we also introduce a way of
representing questions in a knowledge graph that can be made readily executable
as graph queries. We also provide schemes for directive statements, directive
conditional statements, and logical arguments. We argue that semantic units
provide a framework that increases the overall expressivity and cognitive
interoperability of knowledge graphs compared to conventional OWL-based
solutions.
