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This book provides a comprehensive overview of core concepts and technological foundations for continuous engineering of Web streams. It presents various systems and applications and includes real-world examples. Last not least, it introduces the readers to RSP4J, a novel open-source project that aims to gather community efforts in software engineering and empirical research.
The book starts with an introductory chapter that positions the work by explaining what motivates the design of specific techniques for processing data streams using Web technologies. Chapter 2 briefly summarizes the necessary background concepts and models needed to understand the remaining content of the book. Subsequently, chapter 3 focuses on processing RDF streams, taming data velocity in an open environment characterized by high data variety. It introduces query answering algorithms with RSP-QL and analytics functions over streaming data. Chapter 4 presents the life cycle of streaming linked data, it focuses on publishing streams on the Web as a prerequisite aspect to make data findable and accessible for applications. Chapter 5 touches on the problems of benchmarks and systems that analyze Web streams to foster technological progress. It surveys existing benchmarks and introduces guidelines that may support new practitioners in approaching the issue of continuous analytics. Finally, chapter 6 presents a list of examples and exercises that will help the reader to approach the area, get used to its practices and become confident in its technological possibilities.
The second generation of researchers developed Stream Reasoning into RDF Stream Processing. Seminal contributions strengthen the theoretical foundation of the field, which expanded beyond the Semantic Web borders to mix with inductive and deductive Artificial Intelligence. Stream Reasoning can now count contributions in (Temporal) logic, Robotics, Machine Learning, and data integration.
RDF Stream Processing ultimately led to Streaming Linked Data, which this book is about. While the third generation of stream reasoning researchers is approaching seniority, best practices are emerging, and stream processing is rising as the industry’s de facto standard for Big Data engineering and analytics.
This book was envisioned as a resource that collects research efforts and could guide the next generation of researchers, practitioners, and industrial stakeholders. Our goal is to explain the value of data integration when it does not neglect the time-varying nature of data and the continuous essence of some information needs.
This volume focuses on theoretical and practical aspects. It provides a comprehensive perspective of algorithms, systems, and applications for streaming linked data. Finally, it introduces the readers to RSP4J, a novel open-source project that aims to gather community efforts in software engineering and empirical research.
Overall, this book is mainly written for graduate students and researchers in Web and stream data management. It collects research results and will guide the next generation of researchers and practitioners.
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