Integrating data about plans and artifact specifications with data about the actual instances of the entities prescribed by
these provides numerous benefits for tasks such as mission planning, sensor assignment, and asset tasking. However,
doing so raises several issues for data ingest, storage and analytics if a consistent semantics is to be maintained to enable
extensible and unanticipated querying. In this paper, we examine strategies for overcoming these challenges and describe
a method for using the Common Core Ontologies and Modal Relation Ontology to map and integrate data about planned
and existing entities. We demonstrate a solution for ensuring reliable, dynamic and extensible data queries suitable for
highly heterogeneous data sources that is agnostic to implementation requirements. We focus on examples relevant to
sensor capabilities, selection and tasking.
Mark Jensen, Alexander P. Cox, Brian Donohue, and Ron Rudnicki, "Problems with prescriptions: disentangling data about actual versus prescribed entities," Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 106350H (Presented at SPIE Defense + Security: April 16, 2018; Published: 4 May 2018); https://doi.org/10.1117/12.2307718.
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