Stream Reasoning (SR) focuses on developing advanced approaches for applying inference to dynamic data streams; it has become increasingly relevant in various application scenarios such as IoT, Smart Cities, Emergency Management, and Healthcare, despite being a relatively new field of research. The current lack of standardized formalisms and benchmarks has been hindering the comparison between different SR approaches. We proposed a new benchmark, called EnviroStream, for evaluating SR systems on weather and environmental data. The benchmark includes queries and datasets of different sizes. We adopted I-DLV-sr, a recently released SR system based on Answer Set Programming, as a baseline for query modelling and experimentation. We also showcased continuous online reasoning via a web application.

EnviroStream: A Stream Reasoning Benchmark for Environmental and Climate Monitoring

Mastria, Elena;Pacenza, Francesco;Zangari, Jessica;Calimeri, Francesco;Perri, Simona;Terracina, Giorgio
2023-01-01

Abstract

Stream Reasoning (SR) focuses on developing advanced approaches for applying inference to dynamic data streams; it has become increasingly relevant in various application scenarios such as IoT, Smart Cities, Emergency Management, and Healthcare, despite being a relatively new field of research. The current lack of standardized formalisms and benchmarks has been hindering the comparison between different SR approaches. We proposed a new benchmark, called EnviroStream, for evaluating SR systems on weather and environmental data. The benchmark includes queries and datasets of different sizes. We adopted I-DLV-sr, a recently released SR system based on Answer Set Programming, as a baseline for query modelling and experimentation. We also showcased continuous online reasoning via a web application.
2023
big data, stream reasoning, knowledge representation and reasoning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/355238
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