Learning semantic web technologies with the web-based SPARQLTrainer

2010 ◽  
Author(s):  
Daniel Gerber ◽  
Marvin Frommhold ◽  
Michael Martin ◽  
Sebastian Tramp ◽  
Sören Auer
Keyword(s):  
Semantic Web ◽  
Semantic Web Technologies ◽  
Web Based ◽  
Web Technologies ◽  
The Web

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.

Web Data Quality

2014 ◽  
Vol 10 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Amrapali Zaveri ◽  
Andrea Maurino ◽  
Laure-Berti Equille
Keyword(s):  
Semantic Web ◽  
Data Quality ◽  
Linked Data ◽  
Web Data ◽  
Semantic Web Technologies ◽  
Future Directions ◽  
Web Technologies ◽  
Current State ◽  
Web Of Data ◽  
The Web

The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify new challenges that are specific to the Web of Data and provide insights into the current progress and future directions for each of those challenges.

Applying Semantic Web Technologies to Meet the Relevant Challenge of Customer Relationship Management for the U.S. Academic Libraries in the 21st Century Using 121 e-Agent Framework

2011 ◽  
pp. 284-311
Author(s):  
Sharon Q. Yang ◽  
Amanda Xu
Keyword(s):  
Semantic Web ◽  
21St Century ◽  
Academic Libraries ◽  
Trust Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Web Technologies ◽  
Social Semantic Web ◽  
The Web

The main contributions of the chapter are 1) defining relevance challenge of CRM for U.S. academic libraries in the 21st century and applying social Semantic Web technologies to address the relevance challenge of CRM using 121 e-Agent framework in the Web as an infrastructure; 2) binding OLTP, OLAP, and Online Ontological Processing to social Semantic Web applications in CRM; 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications; 4) making the approach extensible to address relevance challenge of CRM in other fields.

A URI is Worth a Thousand Tags

2011 ◽  
pp. 279-302 ◽  
Author(s):  
Alexandre Passant ◽  
Philippe Laublet ◽  
John G. Breslin ◽  
Stefan Decker
Keyword(s):  
Semantic Web ◽  
User Generated Content ◽  
Social Web ◽  
Enterprise 2.0 ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Social ◽  
Web Of Data ◽  
Accepted Practice ◽  
The Web

Although tagging is a widely accepted practice on the Social Web, it raises various issues like tags ambiguity and heterogeneity, as well as the lack of organization between tags. We believe that Semantic Web technologies can help solve many of these issues, especially considering the use of formal resources from the Web of Data in support of existing tagging systems and practices. In this article, we present the MOAT—Meaning Of A Tag—ontology and framework, which aims to achieve this goal. We will detail some motivations and benefits of the approach, both in an Enterprise 2.0 ecosystem and on the Web. As we will detail, our proposal is twofold: It helps solve the problems mentioned previously, and weaves user-generated content into the Web of Data, making it more efficiently interoperable and retrievable.

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.

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