"MBSE without a process-based data architecture is just a random set of characters"

This presentation focuses on the importance of developing a Process-Based Data Architecture as part of pursuing a Model Based Systems Engineering Methodology. The purpose of this presentation is to introduce the user to best practices in developing a Model Based Systems Engineering (MBSE) approach, focusing on the definition of the Data Architecture.

A Process-based Data Architecture provides an understanding of what information is needed to effectively execute the enterprise's business processes and provides a framework for effectively managing the enterprise's information environment.   It provides a representation of data artifacts and data assets that classifies and defines all data entities, their attributes, and associations to facilitate knowledge of how data is produced, managed, and shared in different contexts of use.  The Data Architecture provides identification, management, interoperability, and integration of information across business or organizational elements needed to support Product Data Life-cycle Management goals.  It also ensures that data needed by programs and are identified and managed to provide traceability of data used in decision making. 

The Data Architecture is the foundation for a solid Model-Based Systems Engineering (MBSE) approach.  A well-defined process-based data architecture will facilitate: standardization (definitions, stakeholder concern viewpoints, etc.); uncovering document based process flaws; adherence process compliance audits; Interoperability and data exchange; data integration and interoperability; application/tool schema and methodology development; and definition of IT requirements.