Industrial Internet of Things (IIoT) systems connect a plethora of smart devices, such as
sensors, actuators, and controllers, to enable efficient industrial productions in manners …

Digital twins (DTs) are a powerful mechanism for representing complex industrial assets
such as oil platforms as digital models. These models can facilitate temporal analyses and …

Abstract An Industrial Internet of Things (IoT) is a network of intelligent industrial equipment
such as trains and power generating turbines that collect and share large amounts of data …

Industrial rule-based diagnostic systems are often data-dependant in the sense that they rely
on specific characteristics of individual pieces of equipment. This dependence poses …

Streaming analytics that requires integration and aggregation of heterogeneous and
distributed streaming and static data is a typical task in many industrial scenarios including …

Radio-Frequency Identification (RFID) system technology is a key element for the realization
of the Industry 4.0 vision, as it is vital for tasks such as entity tracking, identification and asset …

Rules over a Knowledge Graph (KG) capture interpretable patterns in data and various
methods for rule learning have been proposed. Since KGs are inherently incomplete, rules …

Rule-based diagnostics of equipment is an important task in industry. In this paper we
present how semantic technologies can enhance diagnostics. In particular, we present our …

Constraints have traditionally been used to ensure data quality. Recently, several constraint
languages such as SHACL, as well as mechanisms for constraint validation, have been …

The emergence of Industry 4.0 has heralded notable progress in manufacturing processes,
utilizing sophisticated sensing and data analytics technologies to maximize efficiency. A vital …