ABSTRACT
So far we have addressed different aspects of RDF and Linked Data management, from modeling to query processing or reasoning. However, in most cases these tasks and operations are applied to static data. For streaming data, which is highly dynamic and potentially infinite, the data management paradigm is quite different, as it focuses on the evolution of data over time, rather that on storage and retrieval. Despite these differences, data streams on the Web can also benefit from the exposure of machine-readable semantic content as seen in the previous chapters. Semantic Web technologies such as RDF and SPARQL have been applied for data streams over the years, in what can be broadly called Linked Data Streams.
