Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Semantic Stream Processing

  • Danh Le-Phuoc
  • Manfred HauswirthEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_287

Synonyms

Definitions

Semantic stream processing (SSP) refers to a set of models, principles, and techniques for analyzing and processing stream data by exploiting semantic structures which are explicitly or implicitly embedded in stream data elements. Such “semantic streams” are represented as sequences of temporal graphs linking human-machine understandable semantics and computational primitives. Semantic stream processing approaches leverage reasoning capabilities through formally defined rules to automate and optimize their continuous processing flows formulated in high-level abstract concepts and relationships.

Overview

Billions of sensors being distributed across the globe are continuously streaming data about the physical world around us. The stream data generated by networks of sensors enables us to detect and identify a multitude of things, from simple phenomena to complex events and situations. However, the lack of integration and...

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Open Distributed SystemsTechnical University of BerlinBerlinGermany
  2. 2.Fraunhofer FOKUSBerlinGermany