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As machine learning is increasingly making decisions about hiring or health care, we want AI to treat ethnic and socioeconomic groups fairly. Fairness is currently measured by comparing the average accuracy of reasoning across groups. We argue that ...

The planning process in the UK is a highly complex system, developed over many decades, and is in the process of rapid transitions into digital planning. Among these transformations is a desire to move from an outputs-based assessment to an outcomes-...

Early warning systems (EWS) for electrical grid infrastructure have played a significant role in the efficient management of electricity supply in natural hazard prone areas. Modern EWS rely on scientific methods to analyze a variety of Earth ...

Monitoring indoor air quality is becoming crucial as people spend most of their time indoors. In recent years, respiratory problems such as chronic obstructive pulmonary disease and asthma appear as among the common diseases that are the reasons for ...

In this demonstration, we propose an AQ-SCIENCE (Air Quality - Smart Cities with IoT-ENabled Citizen Engagement) framework to enhance citizen engagement with an IoT-enabled LCS (low-cost sensors) monitoring kit and platform. Our LCS kits and user study ...

Internet of Things (IoT) platforms are responsible for overall data processing in the IoT System. This ranges from analytics and big data processing to gathering all sensor data over time to analyze and produce long‐term trends. However, this ...

Different cloud services offer platforms for IoT big data analytics and processing, albeit at prohibitively high requirements for resources like memory and bandwidth, to constrained IoT devices. Employing edge computing helps lower some of those ...

The availability of online documents that describe domain-specific information provides an opportunity in employing a knowledge-based approach in extracting information from web data. This research proposes a novel comprehensive semantic knowledge-based ...

Today’s factories are considered as smart ecosystems with humans, machines and devices interacting with each other for efficient manufacturing of products. Industry 4.0 is a suite of enabler technologies for such smart ecosystems that allow ...

Tunnel maintenance requires complex decision making, which involves pathology diagnosis and risk assessment, to ensure full safety while optimising maintenance and repair costs. A Decision Support System (DSS) can play a key role in ...

• A pioneering semantically based decision system for intelligent tunnel diagnosis.

Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles four technical contributions that significantly advance the state-of-the-art in Semantic Web of Things for Industry 4.0 including the use of Semantic Web ...

Within manufacturing processes, faults and failures may cause severe economic loss. With the vision of Industry 4.0, artificial intelligence techniques such as data mining play a crucial role in automatic fault and failure prediction. However, due to the ...

The evolution of IoT has revolutionized industrial automation. Industrial devices at every level such as field devices, control devices, enterprise level devices etc., are connected to the Internet, where they can be accessed easily. It has significantly ...

The IoT landscape is characterized by a fragmentation of standards, platforms and technologies, often scattered among different vertical domains. To prevent the market to continue to be fragmented and power-less, a protocol-independent semantic layer can ...

Semantically rich descriptions of manufacturing machines, offered in a machine-interpretable code, can provide interesting benefits in Industry 4.0 scenarios. However, the lack of that type of descriptions is evident. In this paper we present the ...

This paper investigates how to facilitate users’ exploration through data graphs. The prime focus is on knowledge utility, i.e. increasing a user’s domain knowledge while exploring a data graph, which is crucial in the vast number of user-facing semantic ...

Streaming events are on the increase in various industries, with applications needing data analysed rapidly for real-time detection. A large amount of data from multiple sensors streamed simultaneously is creating a new challenge for instantaneous ...

Modern Early Warning Systems (EWS) rely on scientific methods to analyse a variety of Earth Observation (EO) and ancillary data provided by multiple and heterogeneous data sources for the prediction and monitoring of hazard events. Furthermore, through ...

Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles three technical contributions that significantly advance the state-of-the-art in exploration of semantic data using semantic web techniques and technologies.

RDF Graph Summarization pertains to the process of extracting concise but meaningful summaries from RDF Knowledge Bases (KBs) representing as close as possible the actual contents of the KB both in terms of structure and data. RDF Summarization allows ...

Nowadays it is becoming increasingly necessary to query data stored in different datasets of public access, such as those included in the Linked Data environment, in order to get as much information as possible on distinct topics. However, users have ...