The explosion of data volumes generated by an increasing number of applications is
strongly impacting the evolution of distributed digital infrastructures for data analytics and …

Abstract The Stream Reasoning research paradigm aims to target application domains that
need to solve both data variety and velocity at the same time. Many of these domains benefit …

This PhD project proposes the theoretical and technological foundations of an approach for
decentralized processing of streaming knowledge graphs, where autonomous reasoners …

Video streams are becoming ubiquitous in smart cities and traffic monitoring. Recent
advances in computer vision with deep neural networks enable querying a rich set of visual …

We present a knowledge graph management system designed to run on Edge computing
devices that handles high-frequency data streams. During the design phase, we took into …

This position paper presents ThothSP, a Semantic Programming framework with the aim of
lowering the coding effort in building smart applications on the Device-Edge-Cloud …

Even though data is continually being produced by a wide range of services, harnessing this
data in an effective manner at different levels of abstraction is challenging. In this vision …

Streaming Linked Data represents a domain within the Semantic Web dedicated to
incorporating Stream Reasoning capabilities into the Semantic Web stack to address …

Many data-intensive applications, including smart logistics, smart cities, intelligent factories,
etc. have been made possible by the Internet of Things (IoT). Due to the large amounts of …

We present CQELS 2.0, the second version of Continuous Query Evaluation over Linked
Streams. CQELS 2.0 is a platform-agnostic federated execution framework towards semantic …