Enterprises choose Enterprise Architecture (EA) solution, in order to overcome dynamic business challenges and in coordinate various enterprise elements. In this article, a solution is suggested for the Enterprise Architecture development. The solution focuses on architecture data in the Enterprise Architecture development process. Data-centric architecture approach is preferred product-centric architecture approach. We suggest using Enterprise Ontology (EO) as context for collecting architecture data; Enterprise Ontology enhances quality of architecture data and lead to effective architecture results for decision-making. First, Enterprise is modeled using the ontology. Then how collecting Enterprise Architecture data based on the Enterprise Ontology is explained. Finally, the results and advantages of the solution are demonstrated.

Most of the refinement approach is about functional property of systems. Non-functional properties are as important as functional one. Without an accurate approach for specifying and refining their behaviors, software models will be regarded as imperfect and imprecise, and as a result, software systems cannot be generated correctly. Therefore, how to model such behaviors and how to stepwise refine these behaviors automatically, have become two critical problems in Model Driven Development. In this paper we present an approach for Non-functional refinement in model driven development using high order transformation languages and traceability property of them. We extend the idea of model refinement to non-functional properties of software and propose a stepwise refinement framework with conformance checking between abstract and concrete descriptions of system model using model transformation. The approach is extendable to all quantitative and quantitative non-functional properties.