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 …

The nature of Web data is changing. The popularity of news feeds and social media, the rise
of the Web of Things, and the adoption of sensor technologies are examples of streaming …

With ever increasing data volumes, large compute clusters that process data in a distributed
manner have become prevalent in industry. For distributed stream processing platforms …

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 …

Storm has been a popular distributed real-time computation system for stream data
processing, which currently provides an even scheduler to distribute all executors and …

Nowadays, high volumes of data are generated and published at a very high velocity,
producing heterogeneous data streams. This has led researchers to propose new systems …

Stream processing has recently gained a prominent role in Computer Science research.
From networks or databases to information theory or programming languages, a lot of work …

In the last years, there has been an increase in the amount of real-time data generated.
Sensors attached to things are transforming how we interact with our environment …

Events on the Web are increasingly being produced in the form of data streams, and are
present in many different scenarios and applications such as health monitoring …

Recently, semantic data streams were proposed as a solution to cope with the heterogeneity
of the original streams. However, nowadays, huge volumes of data are produced on the …