Keywords: Conceptual modeling, Enterprise Modeling

Keywords: Enterprise Architecture Management, Education, Survey
Astract: Enterprise architecture (EA), although matured in more than 30 years of ongoing research, receives more importance with the increasing dependency of business in IT and the growing complexity of IT systems. The integrated management of a companies’ goals, structures, and processes with respect to the business and IT elements, as well as the representation of impacts triggered by planned changes is educated in different ways at many universities all over the world. There are several techniques, methods, tools, and approaches to transfer the knowledge from the educators to the students, giving them the qualification to support their future employers in handling the EA challenges modern companies are facing. This work gives a detailed comparative analysis of more than twenty international educational offers regarding Enterprise Architecture Management, carves out the commonalities and finds two prototypical courses as a best-practice combining the strongest matches for Business Informatics and Computer Science studies alike.

Keywords: Conceptual Modeling, Design method, Enterprise Modeling, User orientation
Astract: Enterprise Modeling is far from its maximum potential. An important reason is that opposing stakeholder concerns lead to the existence of context-dependent models that are not mutually related, resulting in an inconsistent enterprise model landscape. This causes problems regarding unsustainable model utilization, since models are not used across different focal areas and over a longer period of time. The aim of our research project is to increase the value of Enterprise Modeling by creating a design method to support users in designing practically applicable models and a model integration method to integrate locally created models into an overarching enterprise model landscape that maintains model consistency.

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Keywords: conceptual modeling, model-driven engineering, model transformation, graph-based analysis, knowledge graphs
Astract: Core assets of enterprise architecture (EA) are its models. They encapsulate enterprise structure and IT knowledge by providing a holistic view of an organization that can drive decision-making. For making good decisions, it is necessary to have an excellent overview and to know how to analyze the model to gain information that different business stakeholders need. From the perspective of history, EA has evolved a lot, and the models have become larger and more complex. Models’ change in size and complexity requires other techniques to analyze the model since the analysis of models in their raw form can exceed human capabilities by far. Therefore current approaches focus on studying partial views over the model, thus providing a partial valuation. This thesis proposes a slightly different approach to cope with EA analysis. The method is based on transforming conceptual models into graphs and analyzing the model in a graph-based manner by using knowledge and possibilities from graph theory. To put this into the real world, we have developed a generic framework and implemented it in the prototype platform, which we call CM2KG. The platform allows analysts to upload different models created in industry-standard tools and transform them into a standardized graph format. From there on, it becomes possible for them to visualize and interact with the model using multiple techniques, query the whole model, and define custom functions that will provide valuable information. We discuss some basic examples for each part to scratch the surface of what is possible. We also put one existing application of EA analysis into the perspective of this approach by implementing queries that are used to identify smells in EA models.