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RDM1: Research Data in Mathematics Location: G309 Session Chair: Moritz Schubotz Session Chair: Olaf Teschke | |
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MaRDIflow: Semantically Enriched Computational Workflows via Domain Ontology Integration 1: TU Ilmenau, Germany; 2: Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany Computational Science and Engineering relies on complex, multi-step workflows that combine simulations, data processing, and parameter-driven analyses across heterogeneous environments. Ensuring reproducibility in such settings requires not only abstract workflow descriptions but also semantically rich metadata that is interoperable across domains. In this work, we present MaRDIflow, a lightweight, metadata-driven workflow framework developed within the MaRDI consortium for research data management in the mathematical sciences. MaRDIflow executes workflows through explicit input–output relationships between components, enabling structured metadata descriptions at different abstraction levels. Redundant representations of models, code, and data are supported to strengthen reproducibility and reuse. To address semantic interoperability, MaRDIflow integrates domain specific ontologies via RESTful APIs and SPARQL endpoints. A modular ontology layer, built on an extensible abstract base class, allows for integration of domain-specific ontologies with minimal effort. With that, workflow components and their metadata to can be aligned dynamically with standardized vocabularies during both construction and execution. As a concrete example, we integrate Voc4Cat, a domain-specific SKOS vocabulary from the NFDI4Cat consortium. Through this integration, knowledge graphs are used to represent and query relationships across workflow layers, supporting automated discovery, validation, and consistent interpretation of data. The presented use cases demonstrate how combining workflow descriptions with domain ontologies enhance semantic consistency, interoperability, and reproducibility. This work further highlights the practical role of application ontologies and lays the groundwork for extending MaRDIflow with additional NFDI ontologies across disciplines. | |
