Problems with prescriptions: disentangling data about actual versus prescribed entities

Mark Jensen; Alexander P. Cox; Brian Donohue; Ron Rudnicki

doi:10.1117/12.2307718

4 May 2018 Problems with prescriptions: disentangling data about actual versus prescribed entities

Mark Jensen, Alexander P. Cox, Brian Donohue, Ron Rudnicki

Proceedings Volume 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX; 106350H (2018) https://doi.org/10.1117/12.2307718
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

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.

Conference Presentation

Citation Download Citation

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 (4 May 2018); https://doi.org/10.1117/12.2307718

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