# RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and Practice

arXiv: https://arxiv.org/abs/2311.14540 · HTML: https://mlsanity.com/paper/2311.14540/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 88 references that are in the map.
- First posted on arXiv 24 Nov 2023.

## Builds on (most cited first, 9 of 9)

- [Broadening the Scope of Nanopublications](https://mlsanity.com/paper/1303.2446/) (2013)
- [Best Practices for Implementing FAIR Vocabularies and Ontologies on the Web](https://mlsanity.com/paper/2003.13084/) (2020)
- [Living Literature Reviews](https://mlsanity.com/paper/2111.00824/) (2021)
- [A Survey of RDF Data Management Systems](https://mlsanity.com/paper/1601.00707/) (2016)
- [RMLStreamer-SISO: an RDF stream generator from streaming heterogeneous data](https://mlsanity.com/paper/2210.14599/) (2022)
- [Stream Containers for Resource-oriented RDF Stream Processing](https://mlsanity.com/paper/2202.13630/) (2022)
- [Ontology Reuse: the Real Test of Ontological Design](https://mlsanity.com/paper/2205.02892/) (2022)
- [Efficient RDF Streaming for the Edge-Cloud Continuum](https://mlsanity.com/paper/2207.04439/) (2022)
- [RiverBench: an Open RDF Streaming Benchmark Suite](https://mlsanity.com/paper/2305.06226/) (2023)

## Abstract (arXiv)

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.