scholarly journals Semantic Web Mining using RDF Data

2016 ◽  
Vol 133 (10) ◽  
pp. 14-19 ◽  
Author(s):  
V. A. ◽  
Amruta A.
Keyword(s):  
Semantic Web ◽  
Web Mining ◽  
Rdf Data

Semantic Web Standards for Publishing and Integrating Open Data

2014 ◽  
pp. 28-47
Author(s):  
Axel Polleres ◽  
Simon Steyskal
Keyword(s):  
Semantic Web ◽  
World Wide ◽  
Open Data ◽  
Standard Data ◽  
Web Standards ◽  
Web Of Data ◽  
Structured Information ◽  
Potential Risks ◽  
Rdf Data ◽  
The Web

The World Wide Web Consortium (W3C) as the main standardization body for Web standards has set a particular focus on publishing and integrating Open Data. In this chapter, the authors explain various standards from the W3C's Semantic Web activity and the—potential—role they play in the context of Open Data: RDF, as a standard data format for publishing and consuming structured information on the Web; the Linked Data principles for interlinking RDF data published across the Web and leveraging a Web of Data; RDFS and OWL to describe vocabularies used in RDF and for describing mappings between such vocabularies. The authors conclude with a review of current deployments of these standards on the Web, particularly within public Open Data initiatives, and discuss potential risks and challenges.

Integrating Web Portals with Semantic Web Services

2012 ◽  
pp. 326-336
Author(s):  
César J. Acuña ◽  
Mariano Minoli ◽  
Esperanza Marcos
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Data Integration ◽  
Methodological Approach ◽  
Integrated Systems ◽  
Semantic Web Services ◽  
Web Portals ◽  
Web Portal ◽  
Integration Architecture

Several systems integration proposals have been suggested over the years. However these proposals have mainly focused on data integration, not allowing users to take advantage of services offered by Web portals. Most of the mentioned proposals only provide a set of design principles to build integrated systems and lack in suggesting a systematic way of how to develop systems based on the integration architecture they propose. In previous work we have developed PISA (Web Portal Integration Architecture)—a Web portal integration architecture for data and services—and MIDAS-S, a methodological approach for the development of integrated Web portals, built according to PISA. This work shows, by means of a case study, how both proposals fit together integrating Web portals.

scholarly journals Semantic Web Portal in University Research Community Framework

2012 ◽  
Vol 2 (6) ◽  
pp. 449
Author(s):  
Rahmat Hidayat ◽  
Yazrina Yahya ◽  
Shahrul Azman Mohd Noah ◽  
Mohd Zakree Ahmad ◽  
Abdul Razak Hamdan
Keyword(s):  
Semantic Web ◽  
Research Community ◽  
University Research ◽  
Web Portal

scholarly journals Accessing biological data in R with semantic web technologies

2014 ◽  
Author(s):  
Egon Willighagen
Keyword(s):  
Semantic Web ◽  
Brca1 Gene ◽  
Database Systems ◽  
Biological Data ◽  
Biological Database ◽  
Semantic Web Technologies ◽  
Data Set ◽  
Web Technologies ◽  
Web Standards ◽  
Rdf Data

Background. Semantic Web technologies are increasingly used in biological database systems. The improved expressiveness show advantages in tracking provenance and allowing knowledge to be more explicitly annotated. The list of semantic web standards needs a complementary set of tools to handle data in those formats to use them in bioinformatics workflows. Methods. The approach proposed in this paper uses the Apache Jena library to create an environment where semantic web technologies can be use in the statistical environment R. The code is exposed as two R packages available from the Comprehensive R Archive Network (CRAN). The RJava library and a custom convenience class is used to bridge between R and the Jena library. Results. We here present two examples showing how the Resource Description Framework (RDF) and SPARQL query standards can be employed in R. The first example takes input on BRCA1 SNPs from a BioMart and converts this into a RDF data set. The second example runs a query on an experimental remote SPARQL end point provided by Uniprot, and searches textual annotations of proteins encoded by the BRCA1 gene. The third example shows how the package can be used to handle RDF returned by OpenTox web services. Discussion. The two provided library bring basic semantic web technologies to R. While only a subset of Apache Jena is currently exposed, it provides key methods to deal with RDF data and resources. The libraries are freely available from the CRAN under the Affero GNU Public License version 3: http://cran.r-project.org/web/packages/rrdf/.

Knowledge discovery using SPARQL property path: The case of disease data set

2019 ◽  
pp. 016555151986549
Author(s):  
Enayat Rajabi ◽  
Salvador Sanchez-Alonso
Keyword(s):  
Semantic Web ◽  
Knowledge Discovery ◽  
Query Language ◽  
Data Sets ◽  
Web Portal ◽  
Semantic Web Technologies ◽  
Data Set ◽  
Domain Experts ◽  
Manual Exploration ◽  
Reasoning Engine

The Semantic Web allows knowledge discovery on graph-based data sets and facilitates answering complex queries that are extremely difficult to achieve using traditional database approaches. Intuitively, the Semantic Web query language (SPARQL) has a ‘property path’ feature that enables knowledge discovery in a knowledgebase using its reasoning engine. In this article, we utilise the property path of SPARQL and the other Semantic Web technologies to answer sophisticated queries posed over a disease data set. To this aim, we transform data from a disease web portal to a graph-based data set by designing an ontology, present a template to define the queries and provide a set of conjunctive queries on the data set. We illustrate how the reasoning engine of ‘property path’ feature of SPARQL can retrieve the results from the designed knowledgebase. The results of this study were verified by two domain experts as well as authors’ manual exploration on the disease web portal.

Nested Optional Join for Efficient Evaluation of SPARQL Nested Optional Graph Patterns

2010 ◽  
pp. 281-308
Author(s):  
Artem Chebotko ◽  
Shiyong Lu
Keyword(s):  
Semantic Web ◽  
Relational Databases ◽  
Real Life ◽  
Query Languages ◽  
Efficient Algorithms ◽  
Relational Algebra ◽  
Nested Loops ◽  
Web Data Management ◽  
Rdf Data ◽  
Rdf Query Languages

Relational technology has shown to be very useful for scalable Semantic Web data management. Numerous researchers have proposed to use RDBMSs to store and query voluminous RDF data using SQL and RDF query languages. This chapter studies how RDF queries with the so called well-designed graph patterns and nested optional patterns can be efficiently evaluated in an RDBMS. The authors propose to extend relational algebra with a novel relational operator, nested optional join (NOJ), that is more efficient than left outer join in processing nested optional patterns of well-designed graph patterns. They design three efficient algorithms to implement the new operator in relational databases: (1) nested-loops NOJ algorithm, NL-NOJ, (2) sort-merge NOJ algorithm, SM-NOJ, and (3) simple hash NOJ algorithm, SH-NOJ. Using a real life RDF dataset, the authors demonstrate the efficiency of their algorithms by comparing them with the corresponding left outer join implementations and explore the effect of join selectivity on the performance of these algorithms.

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