RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and Practice
This work addresses a critical research gap for the RDF streaming community by systematizing stream types to improve discussion, integration, and tool interoperability, though it is incremental as it builds on existing literature.
The authors tackled the challenge of diverse RDF stream definitions by creating a novel taxonomy called RDF-STaX, which is embodied in an OWL 2 DL ontology and includes extensive documentation, use cases, and a nanopublications dataset to foster adoption and drive innovation in RDF streaming.
Over the years, RDF streaming was explored in research and practice from many angles, resulting in a wide range of RDF stream definitions. This variety presents a major challenge in discussing and integrating streaming systems, due to the lack of a common language. This work attempts to address this critical research gap, by systematizing RDF stream types present in the literature in a novel taxonomy. The proposed RDF Stream Taxonomy (RDF-STaX) is embodied in an OWL 2 DL ontology that follows the FAIR principles, making it readily applicable in practice. Extensive documentation and additional resources are provided, to foster the adoption of the ontology. Three use cases for the ontology are presented with accompanying competency questions, demonstrating the usefulness of the resource. Additionally, this work introduces a novel nanopublications dataset, which serves as a collaborative, living state-of-the-art review of RDF streaming. The results of a multifaceted evaluation of the resource are presented, testing its logical validity, use case coverage, and adherence to the community's best practices, while also comparing it to other works. RDF-STaX is expected to help drive innovation in RDF streaming, by fostering scientific discussion, cooperation, and tool interoperability.