[BA] Design and Implementation of a Query Interface and DSL for Feature-Term-Based Stream Discovery

In modern systems that integrate heterogeneous data streams from sensors, APIs, and devices, semantic querying is essential for flexible and dynamic data access. Traditional solutions like GraphQL or REST offer limited support for structural matching and polymorphic discovery. Feature Terms, algebraic structures with labeled features and open arity, provide a foundation for semantically rich type descriptions. Extended with Stream Terms, they allow real-time and virtual data sources to be modeled in a uniform, typed way. This thesis focuses on the design and implementation of a semantic query interface and a corresponding DSL for querying such Feature Term–based metadata. The query system will support structural matching, subtyping (subsumption), tag binding, and output projections. Queries will be evaluated against a registry of StreamTerms, allowing users to discover and subscribe to relevant data streams without relying on predefined identifiers. This thesis is conducted in close coordination with a second bachelor thesis focusing on stream modeling and data source integration using FeatureTerms and StreamTerms. The student is expected to align interfaces and data models collaboratively with the parallel project.

Betreuer: Sebastian Thielemann