Open Taiwan Government data recommendation platform using DBpedia and Semantic Web based on cloud computing
International Journal of Web Information Systems
ISSN: 1744-0084
Article publication date: 19 November 2018
Issue publication date: 10 June 2019
Abstract
Purpose
In recent years, governments around the world are actively promoting the Open Government Data (OGD) to facilitate reusing open data and developing information applications. Currently, there are more than 35,000 data sets available on the Taiwan OGD website. However, the existing Taiwan OGD website only provides keyword queries and lacks a friendly query interface. This study aims to address these issues by defining a DBpedia cloud computing framework (DCCF) for integrating DBpedia with Semantic Web technologies into Spark cluster cloud computing environment.
Design/methodology/approach
The proposed DCCF is used to develop a Taiwan OGD recommendation platform (TOGDRP) that provides a friendly query interface to automatically filter out the relevant data sets and visualize relationships between these data sets.
Findings
To demonstrate the feasibility of TOGDRP, the experimental results illustrate the efficiency of the different cloud computing models, including Hadoop YARN cluster model, Spark standalone cluster model and Spark YARN cluster model.
Originality/value
The novel solution proposed in this study is a hybrid approach for integrating Semantic Web technologies into Hadoop and Spark cloud computing environment to provide OGD data sets recommendation.
Keywords
Acknowledgements
The authors would like to thank the National Chung-Shan Institute of Science & Technology(NCSIST), Taiwan for financially supporting this research under Plan No. 106AZ22.
Citation
Chen, I.-C. and Hsu, I.-C. (2019), "Open Taiwan Government data recommendation platform using DBpedia and Semantic Web based on cloud computing", International Journal of Web Information Systems, Vol. 15 No. 2, pp. 236-254. https://doi.org/10.1108/IJWIS-02-2018-0015
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited