Achieving space domain awareness requires the
identification, characterization, and tracking of space objects.
Storing and leveraging associated space object data for purposes
such as hostile threat assessment, object identification, and
collision prediction and avoidance present further challenges.
Space objects are characterized according to a variety of
parameters including their identifiers, design specifications,
components, subsystems, capabilities, vulnerabilities, origins,
missions, orbital elements, patterns of life, processes, operational
statuses, and associated persons, organizations, or nations. The
Space Object Ontology provides a consensus-based realist
framework for formulating such characterizations in a
computable fashion. Space object data are aligned with classes
and relations in the Space Object Ontology and stored in a
dynamically updated Resource Description Framework triple
store, which can be queried to support space domain awareness
and the needs of spacecraft operators. This paper presents the
core of the Space Object Ontology, discusses its advantages over
other approaches to space object classification, and demonstrates
its ability to combine diverse sets of data from multiple sources
within an expandable framework. Finally, we show how the
ontology provides benefits for enhancing and maintaining longterm
space domain awareness.