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<p>Organizations generate and store unprecedented volumes of data, yet the quality of managerial and operational decisions does not improve accordingly. This article argues that the core problem is not insufficient data management, but the absence of an explicit semantic layer. While data are technically controlled, their meaning, contextual relevance, and organizational impact often remain implicit. With the growing use of AI-based and automated decision systems, this deficit becomes a&#xa0;structural risk, as systems operationalize assumptions about meaning that were never explicitly defined.</p><p>The article positions information and decision architecture as the foundation of data governance. It proposes a&#xa0;semantically driven approach centered on organizational responsibilities, using semantic inventories and context-specific information flow diagrams to make meaning, impact, and responsibility explicit.</p>

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Informations- und Entscheidungsarchitektur als Fundament wirksamer Data Governance – von Datenkontrolle zu semantischer Verantwortung

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Rainer Mayr

摘要

Organizations generate and store unprecedented volumes of data, yet the quality of managerial and operational decisions does not improve accordingly. This article argues that the core problem is not insufficient data management, but the absence of an explicit semantic layer. While data are technically controlled, their meaning, contextual relevance, and organizational impact often remain implicit. With the growing use of AI-based and automated decision systems, this deficit becomes a structural risk, as systems operationalize assumptions about meaning that were never explicitly defined.

The article positions information and decision architecture as the foundation of data governance. It proposes a semantically driven approach centered on organizational responsibilities, using semantic inventories and context-specific information flow diagrams to make meaning, impact, and responsibility explicit.