  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.
