12 May 2016 Modular analytics management architecture for interoperability and decision support
Author Affiliations +
Abstract
The Dual Node Decision Wheels (DNDW) architecture is a new approach to information fusion and decision support systems. By combining cognitive systems engineering organizational analysis tools, such as decision trees, with the Dual Node Network (DNN) technical architecture for information fusion, the DNDW can align relevant data and information products with an organization’s decision-making processes. In this paper, we present the Compositional Inference and Machine Learning Environment (CIMLE), a prototype framework based on the principles of the DNDW architecture. CIMLE provides a flexible environment so heterogeneous data sources, messaging frameworks, and analytic processes can interoperate to provide the specific information required for situation understanding and decision making. It was designed to support the creation of modular, distributed solutions over large monolithic systems. With CIMLE, users can repurpose individual analytics to address evolving decision-making requirements or to adapt to new mission contexts; CIMLE’s modular design simplifies integration with new host operating environments. CIMLE’s configurable system design enables model developers to build analytical systems that closely align with organizational structures and processes and support the organization’s information needs.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen Marotta, Max Metzger, Joe Gorman, Amy Sliva, "Modular analytics management architecture for interoperability and decision support", Proc. SPIE 9831, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII, 98310P (12 May 2016); doi: 10.1117/12.2224142; https://doi.org/10.1117/12.2224142
PROCEEDINGS
11 PAGES


SHARE
Back to Top