“Your mission, should you choose to accept it,” is to boldly incorporate, and correlate, data from various disciplines into the system design and analysis process via a digital engineering ecosystem. The Department of Defense defines Digital Engineering as an integrated digital approach that uses authoritative sources of system data and models as a continuum across disciplines to support lifecycle activities from concept through disposal.
Given the wide-range of engineering and analysis needs throughout the system’s lifecycle, multiple methods, processes, and tools are used to produce data that is ultimately used to make decisions. These method, processes, and tools can vary widely, leaving the AoA engineering team to “splice together” the disparate data to portray a comprehensive depiction of analysis of the various alternatives. However, just because the data is “spliced together” does not mean the data is correlated. Digital engineering focuses on the virtual representation of the system by fostering an ecosystem that assembles all relevant perspectives (i.e. conceptual, logical, physical) of the system, by sharing authoritative data and models. While data and models are shared within the ecosystem, they retain their methodological identity in their native format and environment.
To contemplate the exchange of data in a DE ecosystem, the discussion must be expanded to an ontology base, a structure to define relationships, and by extension to data dictionaries from the various contributing models. A parsimonious ontology allows system entities to be reduced to their atomic level, thus enabling the correlation of data between different technical disciplines and disparate methods, processes, and models. The CDM comprehensively represents the system of interest throughout the system lifecycle, from multiple perspectives (I.e. physical, logical, conceptual), thus allowing for the exploration of the system holistically.
This presentation considers the importance of designing a parsimonious ontology, and CDM, to correlate data from various methods, processes, and models to represent the system holistically. This presentation will first explore how the terms defined in data within each model can be related to parsimonious entity classes in a well-defined ontology. Second, it examines how a common ontology will allow each organization to use the methods, processes, and tools that best fits their analysis needs, while still being able to correlate system data. Lastly, this presentation explores how a conceptual data model can be used to describe a generic model structure based on the common ontology. This representation allows disparate system data to be correlated, which will facilitate more insightful engineering and analysis of the system.
Intended audience: DoD Acquisition and Engineering professionals
References for Deeper Learning:
Speaker:
Dr. Warren Vaneman ESEP, Professor of Practice, Naval Postgraduate School