Federated Data Management2021HT
A federated database system is a collection of multiple autonomous database
systems, which we refer to as federation members. The autonomy of these
federation members is a key aspect; that is, they may be created and operated
independent from one another by different stakeholders. Integrating them into a
federated system enables users to run queries and analyses that cannot be
answered based on the data of any single federation member alone.
While first approaches to building such federated systems emerged in the 1980s, in recent years we are seeing renewed interest in such systems for modern data management use cases in contexts such as the Semantic Web, data lakes, and polystores.
The goal of this PhD course is to learn about both the history of such federated database systems and the characteristics of the different contemporary approaches to building such systems.
No of Lectures
approximately 6-8 seminars
The course will be a reading course over 2-3 months with several seminars during which we discuss, compare, and collaboratively distill the characteristics of various approaches to building federated database systems.
Doctoral students in Computer Science with an interest in information systems and database technologies
A good understanding of basic database technologies.
Active participation in the seminars, including 2-3 shorter presentations; written summaries of 2-3 seminar topics and written reviews of approximately 6 related research papers.
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