Abstract
The RDF Stream Processing (RSP) community has proposed several models and languages for continuously querying and reasoning over RDF streams over the last decade. They each have their semantics, making them hard to compare. The variety of approaches has fostered both empirical and theoretical research and led to the design of RSPQL, i.e., a unifying model for RSP. However, an RSP API for the development under RSPQL semantics was still missing. RSP community would benefit from an RSP API because it can foster comparable and reproducible research by providing programming abstractions based on RSPQL semantics. Moreover, it can encourage further development and in-use research. Finally, it can stimulate practical activities such as tutorials, lectures, and challenges, e.g., during the Stream Reasoning Workshop.
In this paper, we present RSP4J, a flexible API for the development of RSP engines and applications under RSPQL semantics. RSP4J offers all the necessary abstractions required for fast-prototyping of RSP engines under the proposed RSPQL semantics. Users can configure it to reproduce the variety of RSP engine behaviors in a comparable software environment. To promote systematic and comparative research, RSP4J is open-source, provides canonical citation, permanent web identifiers, and a comprehensive user guide for developers.
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Notes
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also known as execution semantics.
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For a comprehensive analysis we suggest [21].
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The current window identified by \(\mathbb {W}\) with the oldest closing time instant at t.
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The RSP W3C Community group has started working towards a common syntax and semantics for RSP (https://github.com/streamreasoning/RSP-QL).
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Slowly evolving RDF graph are represented as a (named) Time-Varying Graph too.
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RSPQL determines the evaluation time instant set ET wrt the reporting policy and the input data. Instead, RSP4J serves time as it receives data, i.e., by consuming the streams. Thus, RSP4J ’s ET is built progressively. While the RSPQL’s ET is deterministic, RSP4J ET might not be deterministic in case of distributed computations.
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Acknowledgment
Dr. Tommasini acknowledges support from the European Social Fund via IT Academy program, and from the European Regional Development Funds via the Mobilitas Plus programme (grant MOBTT75). Moreover, the authors would like to acknowledge the support of Robin Keskisärkkä and Daniele Dell’Aglio in earlier versions of this work.
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Tommasini, R., Bonte, P., Ongenae, F., Della Valle, E. (2021). RSP4J: An API for RDF Stream Processing. In: Verborgh, R., et al. The Semantic Web. ESWC 2021. Lecture Notes in Computer Science(), vol 12731. Springer, Cham. https://doi.org/10.1007/978-3-030-77385-4_34
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