This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I "Foundations and Contexts" provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II "Data Space Technologies" subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various "Use Cases and Data Ecosystems" from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several "Solutions and Applications", eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I "Foundations and Contexts" provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II "Data Space Technologies" subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various "Use Cases and Data Ecosystems" from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several "Solutions and Applications", eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.

Daten sind die strategische Ressource des 21. Jahrhunderts. Es findet kein Geschaftsprozess, keine Kommunikation zwischen Geschaftspartnern, keine Wertschoepfung statt, ohne dass die involvierten Personen, Maschinen und IT-Systeme Daten nutzen, erzeugen oder verandern. Trends wie die Digitalisierung, Industrie 4.0 und Social Media tragen ebenfalls dazu bei, dass Datenmanagement zu einer Kernkompetenz fur erfolgreiche Unternehmen dieser Zeit geworden ist. Damit Daten ihren ganzen Wert entfalten koennen, mussen sie stets in angemessener Qualitat zur Verfugung stehen. Dies gilt besonders fur Stammdaten, die zentralen Geschaftsobjekte eines Unternehmens. Dieses Buch zeigt einen ganzheitlichen Ansatz zum qualitatsbewussten Management von Stammdaten auf und richtet sich damit sowohl an Praktiker als auch an die Wissenschaft. Das "Framework fur Stammdatenqualitatsmanagement" wurde im Rahmen des "Competence Center Corporate Data Quality" der Universitat St. Gallen seit dem Jahr 2006 gemeinsam mit Unternehmen aus unterschiedlichen Industrien in zahlreichen praktischen Anwendungen entwickelt und verbessert. Neben den theoretischen Grundlagen raumt das Buch der praktischen Sicht mit 10 Fallstudien grossen Raum ein, die erfolgreich durchgefuhrte Datenqualitatsprojekte praxisnah aufbereiten. Schliesslich fuhrt das Buch noch Methoden und Werkzeuge fur das Datenqualitatsmanagement auf, die (Stamm-)datenmanager bei Projekten im eigenen betrieblichen Umfeld unterstutzen koennen.