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Inhalt dieser Arbeit sind Entwurf und Umsetzung eines Testsystems, das der Befragung menschlicher Probanden zu psychoakustischen Fragestellungen dienen soll. Zu diesem Zweck soll es sowohl das Erstellen und Verwalten von Testszenarien als auch die Befragung registrierter Probanden selbst realisieren. Einzelnen Testfragen können dabei variabel lange Sounddateien zugewiesen werden. Die Speicherung der Fragebögen sowie der erhobenen Daten erfolgt mit Hilfe eines Datenbanksystems. Dabei liegt das Hauptaugenmerk auf einer flexiblen Fragebogenerstellung, um dem Fragesteller genügend Freiraum im Design einräumen zu können.

Die Studie gibt Auskunft über den Umgang mit Medienbrüchen und die Darstellung von Kennzahlen zur Unternehmenssteuerung in der Landwirtschaft. Datenvernetzung und Visualisierung sind die Voraussetzung zur Etablierung von „smart farming“ in der Praxis. In der Landwirtschaft kann ein hybrides Datenmanagement zu der Vernetzung betrieblicher Software beitragen. Dies besteht aus Datenhubs, Datenroutern und bilateralen Schnittstellen. Die Ergebnisse sind richtungsweisend für landwirtschaftliche Unternehmen, Softwareanbieter, Behörden und alle weiteren Teilnehmer im digitalen Ökosystem der Agrardomäne. Redaktionsschluss: 10.10.2021

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Inhalt dieser Arbeit sind Entwurf und Umsetzung eines Testsystems, das der Befragung menschlicher Probanden zu psychoakustischen Fragestellungen dienen soll. Zu diesem Zweck soll es sowohl das Erstellen und Verwalten von Testszenarien als auch die Befragung registrierter Probanden selbst realisieren. Einzelnen Testfragen können dabei variabel lange Sounddateien zugewiesen werden. Die Speicherung der Fragebögen sowie der erhobenen Daten erfolgt mit Hilfe eines Datenbanksystems. Dabei liegt das Hauptaugenmerk auf einer flexiblen Fragebogenerstellung, um dem Fragesteller genügend Freiraum im Design einräumen zu können.

With the ongoing expansion of information technology, new fields of application requiring data management emerge virtually every day. In our knowledge culture increasing amounts of data and work force organized in more creativity-oriented ways also radically change traditional fields of application and question established assumptions about data management. For instance, investigative analytics and agile software development move towards a very agile and flexible handling of data. As the primary facilitators of data management, database systems have to reflect and support these developments. However, traditional database management technology, in particular relational database systems, is built on assumptions of relatively stable application domains. The need to model all data up front in a prescriptive database schema earned relational database management systems the reputation among developers of being inflexible, dated, and cumbersome to work with. Nevertheless, relational systems still dominate the database market. They are a proven, standardized, and interoperable technology, well-known in IT departments with a work force of experienced and trained developers and administrators. This thesis aims at resolving the growing contradiction between the popularity and omnipresence of relational systems in companies and their increasingly bad reputation among developers. It adapts relational database technology towards more agility and flexibility. We envision a descriptive schema-comes-second relational database system, which is entity-oriented instead of schema-oriented; descriptive rather than prescriptive. The thesis provides four main contributions: (1)~a flexible relational data model, which frees relational data management from having a prescriptive schema; (2)~autonomous physical entity domains, which partition self-descriptive data according to their schema properties for better query performance; (3)~a freely adjustable storage engine, which allows adapting the physical data layout used to properties of the data and of the workload; and (4)~a self-managed indexing infrastructure, which autonomously collects and adapts index information under the presence of dynamic workloads and evolving schemas. The flexible relational data model is the thesis\' central contribution. It describes the functional appearance of the descriptive schema-comes-second relational database system. The other three contributions improve components in the architecture of database management systems to increase the query performance and the manageability of descriptive schema-comes-second relational database systems. We are confident that these four contributions can help paving the way to a more flexible future for relational database management technology.

With the ongoing expansion of information technology, new fields of application requiring data management emerge virtually every day. In our knowledge culture increasing amounts of data and work force organized in more creativity-oriented ways also radically change traditional fields of application and question established assumptions about data management. For instance, investigative analytics and agile software development move towards a very agile and flexible handling of data. As the primary facilitators of data management, database systems have to reflect and support these developments. However, traditional database management technology, in particular relational database systems, is built on assumptions of relatively stable application domains. The need to model all data up front in a prescriptive database schema earned relational database management systems the reputation among developers of being inflexible, dated, and cumbersome to work with. Nevertheless, relational systems still dominate the database market. They are a proven, standardized, and interoperable technology, well-known in IT departments with a work force of experienced and trained developers and administrators. This thesis aims at resolving the growing contradiction between the popularity and omnipresence of relational systems in companies and their increasingly bad reputation among developers. It adapts relational database technology towards more agility and flexibility. We envision a descriptive schema-comes-second relational database system, which is entity-oriented instead of schema-oriented; descriptive rather than prescriptive. The thesis provides four main contributions: (1)~a flexible relational data model, which frees relational data management from having a prescriptive schema; (2)~autonomous physical entity domains, which partition self-descriptive data according to their schema properties for better query performance; (3)~a freely adjustable storage engine, which allows adapting the physical data layout used to properties of the data and of the workload; and (4)~a self-managed indexing infrastructure, which autonomously collects and adapts index information under the presence of dynamic workloads and evolving schemas. The flexible relational data model is the thesis\' central contribution. It describes the functional appearance of the descriptive schema-comes-second relational database system. The other three contributions improve components in the architecture of database management systems to increase the query performance and the manageability of descriptive schema-comes-second relational database systems. We are confident that these four contributions can help paving the way to a more flexible future for relational database management technology.