Streaming Linked Data

​Ricardo Tommasini is a maître de conference (Associate Professor) at INSA Lyon. Pior to join LIRIS lab, he was an assistant professor at the University of Tartu, Estonia. Riccardo holds a Ph.D. from the Department of Electronics and Information of the Politecnico di Milano. His thesis, titled *Velocity on the Web*, investigates the velocity aspects that concern the Web environment. His research interests span Stream Processing, Knowledge Graphs, Logics, and Programming Languages.Pieter Bonte is a post-doctoral researcher at the University of Ghent, IMEC, IDLab. He holds a Ph.D. in Computer Science from the University of Ghent. His research focuses on the use of Semantic Web technologies in the IoT, with a specific focus on scalable & distributed reasoning, stream reasoning, and RDF Stream Processing. He is particularly interested in increasing the expressivity of reasoning over high volatile streams. He has been active in several interdisciplinary projects, in which he was able to leverage his research in an industrial setting. Furthermore, he detailed his research at many international conferences.Fabiano Spiga is an Italian independent researcher. He received his MSc in Computer Science from the University of Jyväskylä (Finland) and he is currently an external PhD student at the University of Tartu (Estonia). His interests span from Big Data to Distributed Systems, the Semantic Web, Process Mining and Network Science, with a keen interest in the scalability and optimization of dataflow processes.Emanuele Della Valle is an Associate Professor at the Department of Electronics and Information of the Politecnico di Milano. His research interests covered Big Data, Stream Processing, Semantic Technologies, Data Science, Web Information Retrieval, and Service Oriented Architectures. His work on Stream Reasoning was applied in analyzing Social Media, Mobile Telecom and IoT data streams in collaboration with Telecom Italia,IBM, Siemens, Oracle, Indra, and Statoil.

• 1. General Introduction.- 2. Preliminaries.- 3. Taming Variety and Velocity.- 4. Streaming Linked Data Life Cycle.- 5. Web Stream Processing Systems and Benchmarks.- 6. Exercise Book.

“Streaming linked data (SLD) is the topic of this book, which collects in six chapters the initial challenges, methods, languages, and results reported in about 15 years of research. ... It is definitely a book for researchers and PhD students ... .” (G. Gini, Computing Reviews, June 24, 2025)