Knowledge Graphs (KG) allow for representing inter-connected facts or statements annotated with semantics. In KGs, concepts and entities are typically modeled as nodes while their connections are modeled as directed and labeled edges, creating a graph.
In recent years, KGs have become core components of modern data ecosystems. KGs, as building blocks of many Artificial Intelligence approaches, allow for harnessing and uncovering patterns from the data. Currently, KGs are used in the data-driven business processes of multinational companies like Google, Microsoft, IBM, eBay, and Facebook. Furthermore, thousands of KGs are openly available on the web following the Linked Data (https://lod-cloud.net/) principles.
Goal: In this lecture, students will learn about the foundations of modelling, querying, publishing, and reasoning over KGs. The topics will be complemented with exercises and Jupyter Notebooks (https://jupyter.org/) to show how KG technologies work in practice.
The link for the SoSe 2023 course is https://moodle.ruhr-uni-bochum.de/course/view.php?id=51531
In recent years, KGs have become core components of modern data ecosystems. KGs, as building blocks of many Artificial Intelligence approaches, allow for harnessing and uncovering patterns from the data. Currently, KGs are used in the data-driven business processes of multinational companies like Google, Microsoft, IBM, eBay, and Facebook. Furthermore, thousands of KGs are openly available on the web following the Linked Data (https://lod-cloud.net/) principles.
Goal: In this lecture, students will learn about the foundations of modelling, querying, publishing, and reasoning over KGs. The topics will be complemented with exercises and Jupyter Notebooks (https://jupyter.org/) to show how KG technologies work in practice.
The link for the SoSe 2023 course is https://moodle.ruhr-uni-bochum.de/course/view.php?id=51531
- Kursleiter/in: Maribel Acosta Deibe
Semester: WiSe 2024/25