SBIR-STTR Award

This proposal describes an innovative approach for creating a structured battle-space model, an approach that will allow military experts to directly compose the model rapidly and efficiently. Our approach will eliminate the need for top-down model design and enable faster and cheaper creation of structured content. The conventional approach for building a structured model is top-down: early during system implementation, the engineering team makes its best effort to specify the model. The team effectively has to "get the model right" very early in development. Rather than asking engineers to construct a model top-down during implementation, we will enable users to create structured content directly, from the bottom-up, using SoftPro's implementation of active forms. Why use active forms to build a data model? Forms are, first of all, well-structured collections of terms (i.e., information elements). By looking at the forms users create, we can derive the terms for a model. In addition, by integrating active forms with an associative memory component we can observe how terms are used and learn about the relationships between terms. Information stored in the associative memory will enable developers to understand what users need in a structured model and to refine the implementation of the model

This proposal describes an innovative approach for creating a battle-space data model; an approach that will allow military experts to directly compose the model rapidly and efficiently. Specifically, we propose to build on our Phase 1 effort that integrated CommandLink, an active forms technology, with an associative memory capable of learning about a data model by observing the interactions users have with forms. We will also integrate Cerebra, an ontology and semantic integration tool; Confederation Web, a database concept to facilitate schema-less shared application data; and learning guided authoring systems tools to facilitate user interaction with the system. Our approach will eliminate the need for top-down model design and enable creation of sharable data content without forcing users to define, build, or maintain structured data models, ontologies, or knowledge bases.

Keywords:
DATA MODELING, ONTOLOGY, LEARNING SYSTEM, DATA MODEL COMPOSITION, SHARED DATA MODEL