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 …

In the last few years a new research area, called stream reasoning, emerged to bridge the
gap between reasoning and stream processing. While current reasoning approaches are …

Continuous SPARQL (C-SPARQL) is a new language for continuous queries over streams
of RDF data. CSPARQL queries consider windows, ie, the most recent triples of such …

Pervasive and sensor-driven systems are by nature open and extensible, both in terms of
input and tasks they are required to perform. Data streams coming from sensors are …

Cybersecurity analysts rely on vast volumes of security event data to predict, identify,
characterize, and deal with security threats. These analysts must understand and make …

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

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 …

In hospitals and smart nursing homes, ambient-intelligent care rooms are equipped with
many sensors. They can monitor environmental and body parameters, and detect wearable …

Industry 4.0 paradigm envisions a new generation of collaborative manufacturing system
where all the components are connected exploiting the Industrial Internet of Things (IIoT) …

In the last decade, there has been a growing interest in applying AI technologies to
implement complex data analytics over data streams. To this end, researchers in various …