Graph Databases: From Theory to Practice

Content

Graph databases have emerged as a powerful tool in managing and analyzing interconnected data. As a very prominent example, Google uses a graph database, the so-called Google Knowledge Graph, to populate the information in the info boxes that appear on the right side when searching. This seminar delves into the theory behind graph databases and provides practical insights into their implementation and usage.

The seminar will cover various graph database models, including property graphs and RDF graphs, highlighting their strengths and use cases. Participants will also learn about query languages such as Cypher and SPARQL, and how to leverage them to extract valuable insights from graph data. Moving beyond theory, the seminar will dive into real-world applications of graph databases across diverse domains such as social networks, recommendation systems, fraud detection, and network analysis.

Organization

There will be an initial meeting in the first week of the semester, please see the Moodle Room of the seminar for details. In this initial meeting, we will present and assign topics, so participation is mandatory for taking the seminar.

More up-to-date information will be made available in Moodle in due time, so please register there.