National Enterprise Architecture (EA) is regarded as a catalyst for achieving e-government goals and many countries have given priority to it in developing their e-government plans. Designing a national EA framework which fits the government’s specific needs facilitates EA planning and implementation for public agencies and boosts the chance of EA success. In this paper, we introduce Iran’s national EA framework (INEAF). The INEAF is designed in order to improve interoperability and deal with EA challenges in Iranian agencies.
The Zachman framework is considered to be the most referenced framework for the purpose of enterprise architecture. It is commonplace to compare other frameworks with this basic one in order to show correctness and usability of those frameworks. However, this is more than a fashion, the Zachman framework is actually the best one. Despite of its popularity, the Zachman framework could be a challengeable one in practical situations because there are not enough well-known methods and tools covering all of its aspects. Three major challenges in using this framework, are discussed in this article. These challenges are lack of a methodology, a well-defined repository and a popular modeling notation. Focus of this article is on solving the last problem with the help of notations in UML (Unified Modeling Language) and UML Business Profile. At the first glance the topic seems to be already researched by others, but there are some major distinctions between this work and the others’, which make it a unique one. Most of the other work tried to cover the framework using multiple class diagrams stereotyped in different ways. This work tries to cover the Zachman framework using all of the UML features, especially those, which are convenient in common modeling tools as well as ignoring unfamiliar symobls as it is used by some authors. A case study is used upon which we show how to apply the selected notation on a sample enterprise to develop cells in second and third rows of the framework. Models are tested to consider if they are supporting Zachman rules governing the framework. Furthermore, in order to see if they could be convincing enough, a statistical study is employed. Although results of these tests are relatively acceptable, the problem of inventing new modeling notations is mentioned as an open problem.
Enterprise Architecture (EA) as a discipline that manages large amount of models and information about different aspects of the enterprise, can support decision making on enterprise-wide issues. In order to provide such support, EA information should be amenable to analysis of various utilities and quality attributes. In this regard, we have proposed the idea of characterizing and using enterprise architecture quality attributes. And this paper provides a quantitative AHP-based method toward expert-based EA analysis. Our method proposes a step-by-step process of assessing quality attribute achievement of different scenarios using AHP. By this method, most suitable EA scenarios are selected according to prioritized enterprise utilities and this selection has an important affect on decision making in enterprises. The proposed method also introduces a data structure that contains required information about quality attribute achievement of different EA scenarios in enterprises. The stored asset can be used for further decision making and progress assessment in future. Sensitivity analysis is also part of the process to identify sensitive points in the decision process. The applicability of the proposed method is demonstrated using a practical case study.