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.
Semantic Web Technologies for Big Data Modeling from Analytics Perspective: A Systematic Literature Review
