scholarly journals Interoperable Digital Building Twins Through Communicating Materials and Semantic BIM

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Ana Roxin ◽  
Wahabou Abdou ◽  
William Derigent
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
State Of The Art ◽  
Wireless Sensor ◽  
Construction Process ◽  
Semantic Web Technologies ◽  
Research Issues ◽  
Main Research ◽  
Web Technologies ◽  
Research Domains

AbstractThis paper presents contributions of the ANR McBIM (Communicating Material for BIM) project regarding Digital Building Twins, specifically how Semantic Web technologies allow providing explainable decision-support. Following an introduction stating our understanding of a Digital Building Twin (DBT), namely a lively representation of a buildings' status and environment, we identify five main research domains following the study of main research issues related to DBT. We then present the state-of-the-art and existing standards for digitizing the construction process, Semantic Web technologies, and wireless sensor networks. We further position the main contributions made so far in the ANR McBIM project's context according to this analysis, e.g., sensor placement in the communicating material and explainable decision-support.

Mini-ME Matchmaker and Reasoner for the Semantic Web of Things

2018 ◽  
pp. 262-294 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Of Things ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

The Semantic Web of Things (SWoT) aims to support smart semantics-enabled applications and services in pervasive contexts. Due to architectural and performance issues, most Semantic Web reasoners are often impractical to be ported: they are resource consuming and are basically designed for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper describes Mini-ME (the Mini Matchmaking Engine), a mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering, bonus, difference) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios and experimental performance evaluation are presented on PC (against other popular Semantic Web reasoners), smartphone and embedded single-board computer testbeds.

Semantic Web of Things for Industry 4.0

Semantic Web ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 885-886
Author(s):  
Dhavalkumar Thakker ◽  
Pankesh Patel ◽  
Muhammad Intizar Ali ◽  
Tejal Shah
Keyword(s):  
Semantic Web ◽  
Industry 4.0 ◽  
State Of The Art ◽  
The State ◽  
Special Issue ◽  
Semantic Web Technologies ◽  
Web Of Things ◽  
Web Technologies

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 technologies and techniques in Industry 4.0 solutions.

scholarly journals A Mobile Matchmaker for the Ubiquitous Semantic Web

2016 ◽  
pp. 994-1017 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Internet Of Things ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT). It aims to enable smart semantic-enabled applications and services in ubiquitous contexts. Due to architectural and performance issues, it is currently impractical to use existing Semantic Web reasoners. They are resource consuming and are basically optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper presents Mini-ME, a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios are presented and an experimental performance evaluation is provided both on a PC testbed (against other popular Semantic Web reasoners) and on a smartphone.

Data Integration in the Geospatial Semantic Web

2011 ◽  
pp. 272-293
Author(s):  
Patrick Maué ◽  
Sven Schade
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
Real World ◽  
Relevant Information ◽  
Decision Makers ◽  
Semantic Web Technologies ◽  
Domain Experts ◽  
Web Technologies ◽  
Opening Up ◽  
The Web

Geospatial decision makers have to be aware of the varying interests of all stakeholders. One crucial task in the process is to identify relevant information available from the Web. In this chapter the authors introduce an application in the quarrying domain which integrates Semantic Web technologies to provide new ways to discover and reason about relevant information. The authors discuss the daily struggle of the domain experts to create decision-support maps helping to find suitable locations for opening up new quarries. After explaining how semantics can help these experts, they introduce the various components and the architecture of the software which has been developed in the European funded SWING project. In the last section, the different use cases illustrate how the implemented tools have been applied to real world scenarios.

scholarly journals Weaving a Semantic Web of Credibility Reviews for Explainable Misinformation Detection (Extended Abstract)

2021 ◽  
Author(s):  
Ronald Denaux ◽  
Martino Mensio ◽  
Jose Manuel Gomez-Perez ◽  
Harith Alani
Keyword(s):  
Deep Learning ◽  
Semantic Web ◽  
Computational Model ◽  
State Of The Art ◽  
Learning Systems ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Detection Systems ◽  
Wide Range

This paper summarises work where we combined semantic web technologies with deep learning systems to obtain state-of-the art explainable misinformation detection. We proposed a conceptual and computational model to describe a wide range of misinformation detection systems based around the concepts of credibility and reviews. We described how Credibility Reviews (CRs) can be used to build networks of distributed bots that collaborate for misinformation detection which we evaluated by building a prototype based on publicly available datasets and deep learning models.

Building Integrative Enterprise Knowledge Portals with Semantic Web Technologies

2005 ◽  
pp. 146-188 ◽  
Author(s):  
Torsten Priebe
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
State Of The Art ◽  
Content Management ◽  
The State ◽  
The Internet ◽  
Semantic Web Technologies ◽  
Research Results ◽  
Web Technologies ◽  
Integration Approach

The goal of this chapter is to show how Semantic Web technologies can help build integrative enterprise knowledge portals. Three main areas are identified: content management and metadata, global searching, and the integration of external content and applications. For these three areas the state-of-the-art as well as current research results are discussed. In particular, a metadata-based information retrieval and a context-based port let integration approach are presented. These have been implemented in a research prototype which is introduced in the Internet session at the end of the chapter.

scholarly journals A Mobile Matchmaker for the Ubiquitous Semantic Web

2014 ◽  
Vol 10 (4) ◽  
pp. 77-100 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Internet Of Things ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT). It aims to enable smart semantic-enabled applications and services in ubiquitous contexts. Due to architectural and performance issues, it is currently impractical to use existing Semantic Web reasoners. They are resource consuming and are basically optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper presents Mini-ME, a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios are presented and an experimental performance evaluation is provided both on a PC testbed (against other popular Semantic Web reasoners) and on a smartphone.

Data Integration in the Geospatial Semantic Web

2009 ◽  
Vol 11 (4) ◽  
pp. 100-122 ◽  
Author(s):  
Patrick Maué ◽  
Sven Schade
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
Real World ◽  
Relevant Information ◽  
Decision Makers ◽  
Semantic Web Technologies ◽  
Domain Experts ◽  
Web Technologies ◽  
Opening Up ◽  
The Web

Geospatial decision makers have to be aware of the varying interests of all stakeholders. One crucial task in the process is to identify relevant information available from the Web. In this chapter the authors introduce an application in the quarrying domain which integrates Semantic Web technologies to provide new ways to discover and reason about relevant information. The authors discuss the daily struggle of the domain experts to create decision-support maps helping to find suitable locations for opening up new quarries. After explaining how semantics can help these experts, they introduce the various components and the architecture of the software which has been developed in the European funded SWING project. In the last section, the different use cases illustrate how the implemented tools have been applied to real world scenarios.

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