Stream reasoning studies the application of inference techniques to data characterised by
being highly dynamic. It can find application in several settings, from Smart Cities to Industry …

This paper is a survey of the research topics in the field of Semantic Web, Linked Data and
Web of Data. This study looks at the contributions of this research community over its first …

We study stream reasoning in DatalogMTL—an extension of Datalog with metric temporal
operators. We propose a sound and complete stream reasoning algorithm that is applicable …

An increasing number of use cases require a timely extraction of non-trivial knowledge from
semantically annotated data streams, especially on the Web and for the Internet of Things …

Abstract Enterprise Communication Systems are designed in such a way to maximise the
efficiency of communication and collaboration within the enterprise. With users becoming …

In the Internet of Things (IoT), multiple sensors and devices are generating heterogeneous
streams of data. To perform meaningful analysis over multiple of these streams, stream …

RDF streams are sequences of timestamped RDF statements or graphs, which can be
generated by several types of data sources (sensors, social networks, etc.). They may …

Data streams are becoming omnipresent on the Web. The Stream Reasoning (SR)
paradigm, which combines Stream Processing with Semantic Web techniques, has been …

In big data, data originates from many distributed and different sources in the shape of
audio, video, text and sound on the bases of real time; which makes it massive and complex …

We consider the feasibility of processing billions of RDF triples on a single commodity
machine using streaming and sorting techniques and focusing on RDF processing tasks …