Supporting the Model-Driven Organization Vision through Deep, Orthographic Modeling
In a model-driven organization, all stakeholders are able to deal with information about an organization in the way that best supports their goals and tasks. In other words, they are able to select models of the organization at the optimal level of abstraction (e.g. platform independent) in the optimal form (e.g. graph-based) and with the optimal scope (e.g. a single component). However, no approach exists today that seamlessly supports this capability over the entire life-cycle of organizations and the IT systems that drive them. Enterprise architecture modeling approaches focus on supporting model-based views of the static architecture of organizations (i.e. enterprises) but generally provide little if any support for operational views. On the other hand, business intelligence approaches focus on providing operational views of organizations and usually do not accommodate static architectural views. In order to fully support the model-driven organization (MDO) vision, therefore, these two worlds need to be unified and a common, natural and uniform approach for defining and supporting all forms of views on organizations, at all stages of their life-cycles, needs to be defined and implemented in an efficient and scalable way. This paper presents a vision for achieving this goal based on the notions of deep and orthographic modeling. After explaining the background to the problem and introducing these two paradigms, the paper presents a novel approach for unifying them, along with a prototype implementation and example.
Copyright (c) 2018 Christian Tunjic, Colin Atkinson, Dirk Draheim
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