scholarly journals Biological data integration using Semantic Web technologies

Biochimie ◽  
2008 ◽  
Vol 90 (4) ◽  
pp. 584-594 ◽  
Author(s):  
C. Pasquier
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Biological Data ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Biological Data Integration

scholarly journals The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies

2013 ◽  
Vol 4 (1) ◽  
pp. 6 ◽  
Author(s):  
Toshiaki Katayama ◽  
Mark D Wilkinson ◽  
Gos Micklem ◽  
Shuichi Kawashima ◽  
Atsuko Yamaguchi ◽  
...  
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Life Science ◽  
Science Data ◽  
Semantic Web Technologies ◽  
Web Technologies

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/.

scholarly journals A case study of data integration for aquatic resources using semantic web technologies

2015 ◽  
Author(s):  
Janice M. Gordon ◽  
Nina Chkhenkeli ◽  
David L. Govoni ◽  
Frances L. Lightsom ◽  
Andrea C. Ostroff ◽  
...  
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Semantic Web Technologies ◽  
Aquatic Resources ◽  
Web Technologies

scholarly journals Linked Data Driven Information Systems as an Enabler for Integrating Financial Data

2011 ◽  
pp. 239-270 ◽  
Author(s):  
Seán O’Riain ◽  
Andreas Harth ◽  
Edward Curry
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Information Integration ◽  
Financial Services ◽  
Linked Data ◽  
Financial Data ◽  
Data Sources ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Multiple Data

With increased dependence on efficient use and inclusion of diverse corporate and Web based data sources for business information analysis, financial information providers will increasingly need agile information integration capabilities. Linked Data is a set of technologies and best practices that provide such a level of agility for information integration, access, and use. Current approaches struggle to cope with multiple data sources inclusion in near real-time, and have looked to Semantic Web technologies for assistance with infrastructure access, and dealing with multiple data formats and their vocabularies. This chapter discusses the challenges of financial data integration, provides the component architecture of Web enabled financial data integration and outlines the emergence of a financial ecosystem, based upon existing Web standards usage. Introductions to Semantic Web technologies are given, and the chapter supports this with insight and discussion gathered from multiple financial services use case implementations. Finally, best practice for integrating Web data based on the Linked Data principles and emergent areas are described.

scholarly journals Accessing biological data with semantic web technologies

2013 ◽  
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. 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/.

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