Semantic Middleware Architecture

2013 ◽  
Vol 436 ◽  
pp. 488-496 ◽  
Author(s):  
Dragos Repta ◽  
Ioan Stefan Sacala ◽  
Mihnea Moisescu ◽  
Aurelian Mihai Stanescu
Keyword(s):  
Distributed Systems ◽  
Internet Of Things ◽  
Test System ◽  
Context Aware ◽  
Semantic Technologies ◽  
Research Activity ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
It Systems ◽  
Event Based

Some of the most important features of future IT systems will come from the current research of Semantic Web technologies and distributed systems. Following this idea we set out to implement a middleware solution that builds upon the latest developments of research activity into Internet of Things and, more generally, context-aware systems. These directions where selected because they currently are the main drivers of the research into the applications of semantic technologies. Our focus was mainly on the aspects that we considered to be overlooked by other proposed semantic middleware solutions, such as the support of asynchronous, event based communication and ontology management in distributed systems. The developed middleware was used to build a test system in order to prove its advantages over similar systems that rely on currently used technologies.

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.

Semantic Interation, Text Mining, Tools and Technologies

2015 ◽  
pp. 47-63
Author(s):  
Chandrakant Ekkirala
Keyword(s):  
Text Mining ◽  
Data Integration ◽  
Semantic Integration ◽  
Semantic Technologies ◽  
Integration Technique ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Periodic Data ◽  
Integration Techniques ◽  
Mining Algorithms

Semantic technologies have gained prominence over the last several years. Semantic technologies are explored in detail and semantic integration of data will be outlined. The various data integration techniques and approaches will also be touched upon. Text Mining, different associated algorithms and the various tools and technologies used in text mining will be enumerated in detail. The chapter will have the following sections – 1. Data Integration Techniques • Data Integration Technique – Extraction, Transformation and Loading (ETL) • Data Integration Technique – Data Federation 2. Data Integration Approaches • Need Based Data Integration • Periodic Data Integration • Continuous Data Integration 3. Semantic Integration 4. Semantic Technologies 5. Semantic Web Technologies 6. Text Mining 7. Text Mining Algorithms 8. Tools and Technologies for Text Mining

Knowledge Representation Technologies Using Semantic Web

Web Services ◽  
2019 ◽  
pp. 1068-1076
Author(s):  
Vudattu Kiran Kumar
Keyword(s):  
Semantic Web ◽  
Crucial Role ◽  
World Wide ◽  
Global Information ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Repositories ◽  
The World ◽  
The Web

The World Wide Web (WWW) is global information medium, where users can read and write using computers over internet. Web is one of the services available on internet. The Web was created in 1989 by Sir Tim Berners-Lee. Since then a great refinement has done in the web usage and development of its applications. Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. Semantic web is not a separate web it is an extension to the current web with additional semantics. Semantic technologies play a crucial role to provide data understandable to machines. To achieve machine understandable, we should add semantics to existing websites. With additional semantics, we can achieve next level web where knowledge repositories are available for better understanding of web data. This facilitates better search, accurate filtering and intelligent retrieval of data. This paper discusses about the Semantic Web and languages involved in describing documents in machine understandable format.

Knowledge Representation Technologies Using Semantic Web

2017 ◽  
pp. 158-166
Author(s):  
Vudattu Kiran Kumar
Keyword(s):  
Semantic Web ◽  
Crucial Role ◽  
World Wide ◽  
Global Information ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Repositories ◽  
The World ◽  
The Web

The World Wide Web (WWW) is global information medium, where users can read and write using computers over internet. Web is one of the services available on internet. The Web was created in 1989 by Sir Tim Berners-Lee. Since then a great refinement has done in the web usage and development of its applications. Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. Semantic web is not a separate web it is an extension to the current web with additional semantics. Semantic technologies play a crucial role to provide data understandable to machines. To achieve machine understandable, we should add semantics to existing websites. With additional semantics, we can achieve next level web where knowledge repositories are available for better understanding of web data. This facilitates better search, accurate filtering and intelligent retrieval of data. This paper discusses about the Semantic Web and languages involved in describing documents in machine understandable format.

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.

A State of the Art on Big Data With Semantic Web Technologies

2020 ◽  
pp. 195-216
Author(s):  
Satyaveer Singh ◽  
Mahendra Singh Aswal
Keyword(s):  
Big Data ◽  
Semantic Web ◽  
Database Management ◽  
High Volume ◽  
Semantic Technologies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Past ◽  
Digital World ◽  
Data Heterogeneity

We live in a digital world where a large amount of data is being generated rapidly by various diverse sources with an unprecedented rate. The term Big Data has been coined to represent a large amount of data. But Big Data could not be processed and analysed by traditional database management systems. A number of challenges such as data heterogeneity and diversity are being faced by enterprises due to high volume, variety, and velocity of Big Data. Since the past few years, some research efforts have been attempted to integrate semantic web technologies such as ontologies with Big Data. This integration is paving the way to deal with various issues that are related to the processing of Big Data. This chapter firstly uncovers the fundamentals of Big Data, its characteristics and opportunities, challenges, related current tools, and technologies. Secondly, it tries to highlight the integration of Big Data with semantic web technologies. The promising research is going on to tackle volume and velocity of Big Data by using semantic technologies.

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