scholarly journals Semantic Web Technologies for Data Curation and Provenance

2019 ◽  
Author(s):  
Clifford Brown
Keyword(s):  
Semantic Web ◽  
Measurement Process ◽  
Data Curation ◽  
Science And Engineering ◽  
Semantic Web Technologies ◽  
Meta Data ◽  
Web Technologies ◽  
The World

The Reproducibility issue even if not a crisis, is still a major problem in the world of science and engineering. Within metrology, making measurements at the limits that science allows for, inevitably, factors not originally considered relevant can be very relevant. Who did the measurement? How exactly did they do it? Was a mistake made? Was the equipment working correctly? All these factors can influence the outputs from a measurement process. In this work we investigate the use of Semantic Web technologies as a strategic basis on which to capture provenance meta-data and the data curation processes that will lead to a better understanding of issues affecting reproducibility.

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.

Overview of MERA

2019 ◽  
pp. 219-245
Author(s):  
Daniel Fernández-Álvarez ◽  
José Emilio Labra Gayo ◽  
Daniel Gayo-Avello ◽  
Patricia Ordoñez de Pablos
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
World Wide ◽  
Poor Performance ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Matching Process ◽  
Large Databases ◽  
The World ◽  
Distinguishing Features

The proliferation of large databases with potentially repeated entities across the World Wide Web drives into a generalized interest to find methods to detect duplicated entries. The heterogeneity of the data cause that generalist approaches may produce a poor performance in scenarios with distinguishing features. In this paper, we analyze the particularities of music related-databases and we describe Musical Entities Reconciliation Architecture (MERA). MERA consists of an architecture to match entries of two sources, allowing the use of extra support sources to improve the results. It makes use of semantic web technologies and it is able to adapt the matching process to the nature of each field in each database. We have implemented a prototype of MERA and compared it with a well-known music-specialized search engine. Our prototype outperforms the selected baseline in terms of accuracy.

Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė
Keyword(s):  
Semantic Web ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning

Applying Semantic Web Technologies to Drug Safety Determination

2006 ◽  
Vol 21 (1) ◽  
pp. 82-86 ◽  
Author(s):  
S. Stephens ◽  
A. Morales ◽  
M. Quinlan
Keyword(s):  
Semantic Web ◽  
Drug Safety ◽  
Semantic Web Technologies ◽  
Web Technologies
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