Requirements such as integrated view of the customer or global business process integration make enterprise wide management of master data a prerequisite for achieving business goals. The master data application architecture, as a part of enterprise master data management, plays a critical role in enterprises. Choosing the right master data application architecture is a controversial subject in many enterprises. Unfortunately, the current state of the art in research does not provide sufficient guidance for enterprises dealing with this subject. The paper aims at overcoming this gap in research by presenting a decision model for supporting enterprises in the decision-making process regarding the choice of the right master data application architecture. To design the model, Multiple-Criteria Decision Analysis and Design Science Research Methodology were applied.

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Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders-such as businesses, policy makers, researchers, developers-the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of ''business semantics'', ''business-to-business interoperability'', and ''interoperability standards'' amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a ''real-life'' context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standards.

In der Theorie wird unterschieden zwischen den Konzepten Daten, Informationen und Wissen. Daten stellen die Grundlage von Informationen dar. Werden sie subjektiv in einen Kontext gesetzt, werden sie zu Informationen. Durch die