Challenges and Directions in Formalizing the Semantics of Modeling Languages

Developing software from models is a growing practice and there exist many model-based tools (e.g., editors, interpreters, debuggers, and simulators) for supporting model-driven engineering. Even though these tools facilitate the automation of software engineering tasks and activities, such tools are typically engineered manually. However, many of these tools have a common semantic foundation centered around an underlying modeling language, which would make it possible to automate their development if the modeling language specification were formalized. Even though there has been much work in formalizing programming languages, with many successful tools constructed using such formalisms, there has been little work in formalizing modeling languages for the purpose of automation. This paper discusses possible semantics-based approaches for the formalization of modeling languages and describes how this formalism may be used to automate the construction of modeling tools

A Formal Context Representation Framework for Network-Enabled Cognition

Network-accessible resources are inherently contextual with respect to the specific situations (e.g., location and default assumptions) in which they are used. Therefore, the explicit conceptualization and representation of contexts is required to address a number of problems in Network- Enabled Cognition (NEC). We propose a context representation framework to address the computational specification of contexts. Our focus is on developing a formal model of context for the unambiguous and effective delivery of data and knowledge, in particular, for enabling forms of automated inference that address contextual differences between agents in a distributed network environment. We identify several components for the conceptualization of contexts within the context representation framework. These include jurisdictions (which can be used to interpret contextual data), semantic assumptions (which highlight the meaning of data), provenance information and inter-context relationships. Finally, we demonstrate the application of the context representation framework in a collaborative military coalition planning scenario. We show how the framework can be used to support the representation of plan-relevant contextual information