Reasoning on Knowledge Graphs

Content

In this project group (PG), you will implement a reasoning services into an existing knowledge graph database.

As the amount of data we have grows and as we store more and more data that is too diverse and flexible to fit well into tables of traditional relational databases, graph databases emerge as a flexible and expressive alternative. With the Resource Description Framework (RDF) and the Web Ontology Language (OWL) graphs provide the semantics to reason about data stored and infer implicit knowledge.

You will implement two services based on OWL: Materialization and instance retrieval. Materialization means that implicit knowledge is inferred and added as explicit knowledge to the knowledge base. For retrieving instances, a class expression (= logical formula) is provided. All individuals (= nodes in the graph) that fulfill the formula are returned then.

Requirements

• You must have experience beyond a beginner level in C++. You should be familiar with coding by at least the C++11 Standard, better C++17 or later.
• You must not fear to read formal specifications.
• Some prior knowledge of RDF, OWL or description logics is beneficial but not necessary.
• You should know git, GitHub, CLion and Linux, or be willing to learn your ways around the tools quickly.

Course in PAUL

The PG will be available in PAUL (TBA).

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