Naif Radi Aljohani

Work place: Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia



Research Interests: Computer systems and computational processes, Computational Learning Theory, Computer Architecture and Organization, World Wide Web, Data Structures and Algorithms


Naif Radi Aljohani received his Bachelor’s degree in Computer Education from King Abdulaziz University in 2005, the Master degree in Computer Networks from La Trobe University, Australia, in 2009 and a Ph.D. degree in Computer Science from the University of Southampton, UK, in 2014. Currently, Mr. Naif is working as Assistant Professor at the Faculty of Computing and Information Technology at King Abdulaziz University, Jeddah, Saudi Arabia. His research interests are in the areas of mobile and ubiquitous computing, mobile and ubiquitous learning, learning and knowledge analytics, semantic web, Web Science, technology-enhanced learning and human-computer interaction.

Author Articles
Leveraging the Saudi Linked Open Government Data: A Framework and Potential Benefits

By Afnan M. AlSukhayri Muhammad Ahtisham Aslam Sachi Arafat Naif Radi Aljohani

DOI:, Pub. Date: 8 Jul. 2019

Open data initiatives are a crucial aspect of effective e-governance strategy. They embody aspirations towards sociopolitical values of transparency, trust, confidence, and accountability, pertaining to the relationship between a government and its citizens. The importance of such initiatives is especially important for an emerging economy such as Saudi Arabia which is undergoing rapid social changes directed by a contemporary national vision. The effectiveness of open data initiatives depends strongly on (a) the quality of the data available, (b) the soundness of the methodologies and suitability of platforms used to prepare and present the data, and (c) the ability of the data to facilitate the kinds of insights and social-action that are sought from that data to ensure successful e-governance. This paper investigates the feasibility of current Saudi government open data initiatives in this regard. It assesses existing approaches to improve the effectiveness of open government data through transforming it into linked-open data (using the Resource Description Framework [RDF]) by connecting disparate sources of structured data therein. It proposes to improve existing approaches by suggesting a framework for automating the linking sub-process of existing approaches and organizing the data to be queried through SPARQL. Moreover, it evaluates the potential benefit of this proposal by discussing the kinds of policy insights this could generate which would be difficult without it.

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