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Proceedings Paper

Problems with prescriptions: disentangling data about actual versus prescribed entities
Author(s): Mark Jensen; Alexander P. Cox; Brian Donohue; Ron Rudnicki
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Paper Abstract

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.

Paper Details

Date Published: 4 May 2018
PDF: 9 pages
Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 106350H (4 May 2018); doi: 10.1117/12.2307718
Show Author Affiliations
Mark Jensen, CUBRC, Inc. (United States)
Alexander P. Cox, CUBRC, Inc. (United States)
Brian Donohue, CUBRC, Inc. (United States)
Ron Rudnicki, CUBRC, Inc. (United States)

Published in SPIE Proceedings Vol. 10635:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX
Michael A. Kolodny; Dietrich M. Wiegmann; Tien Pham, Editor(s)

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