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.

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.

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.

How Industry 4.0 Can Benefit From Semantic Web Technologies and Artefacts

2021 ◽  
Vol 13 (4) ◽  
pp. 64-74
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Semantic Web ◽  
Industry 4.0 ◽  
The Internet ◽  
Time Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Real Time Data ◽  
The Internet Of Things

Industry 4.0 is a technology-driven manufacturing process that heavily relies on technologies, such as the internet of things (IoT), cloud computing, web services, and big real-time data. Industry 4.0 has significant potential if the challenges currently being faced by introducing these technologies are effectively addressed. Some of these challenges consist of deficiencies in terms of interoperability and standardization. Semantic Web technologies can provide useful solutions for several problems in this new industrial era, such as systems integration and consistency checks of data processing and equipment assemblies and connections. This paper discusses what contribution the Semantic Web can make to Industry 4.0.

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.

A semantic-based approach for querying linked data using natural language

2016 ◽  
Vol 42 (6) ◽  
pp. 851-862 ◽  
Author(s):  
Mario Andrés Paredes-Valverde ◽  
Rafael Valencia-García ◽  
Miguel Ángel Rodríguez-García ◽  
Ricardo Colomo-Palacios ◽  
Giner Alor-Hernández
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Knowledge Bases ◽  
Semantic Knowledge ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Natural Language Interface ◽  
High Quality Information ◽  
Domain Independent

The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question’s structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users.

Applying Semantic Web Technologies to Provide Feasibility Feedback in Early Design Phases

2019 ◽  
Vol 19 (4) ◽  
Author(s):  
Felix Ocker ◽  
Birgit Vogel-Heuser ◽  
Christiaan J. J. Paredis
Keyword(s):  
Semantic Web ◽  
Product Development ◽  
Process Design ◽  
Development Process ◽  
Batch Processing ◽  
Knowledge Bases ◽  
Product Development Process ◽  
Semantic Web Technologies ◽  
Early Design ◽  
Web Technologies

In the product development process, as it is currently practiced, production is still often neglected in the early design phases, leading to late and costly changes. Using the knowledge of product designers concerning production process design, this paper introduces an ontological framework that enables early feasibility analyses. In this way, the number of iterations between product and process design can almost certainly be reduced, which would accelerate the product development process. Additionally, the approach provides process engineers with possible production sequences that can be used for process planning. To provide feasibility feedback, the approach presented relies on semantic web technologies. An ontology was developed that supports designers to model the relations among products, processes, and resources in a way that allows the use of generic Sparql Protocol And RDF Query Language (SPARQL) queries. Future applicability of this approach is ensured by aligning it with the top-level ontology Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE). We also compare the ontology’s universals to fundamental classes of existing knowledge bases from the manufacturing and the batch processing domains. This comparison demonstrates the approach’s domain-independent applicability. Two proofs of concept are described, one in the manufacturing domain and one in the batch processing domain.

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