Muhammad Ahtisham Aslam

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

E-mail: maaslam@kau.edu.sa

Website:

Research Interests: Computer Science & Information Technology, Computational Science and Engineering, Social Information Systems, Data Structures and Algorithms

Biography

Muhammad Ahtisham Aslam received the Master degree in computer science from Hamdard University, Lahore, Pakistan, in 2002 and a Ph.D. degree from University of Leipzig, Leipzig, Germany in 2007. From 2003 to 2007, he had been working as Research Assistant and Ph.D. student at University of Leipzig, Leipzig, Germany. His research interest includes semantic web, linked open data, data science, and social network. Muhammad A. Aslam is currently working as Assistant Professor at Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia. He has been working as Senior Staff Researcher at Artificial Intelligence Lab, Knowledge Technology Cluster, Malaysian Institute of Microelectronic Systems (MIMOS), Kuala Lumpur, Malaysia. He also has been working as Assistant Professor at COMSATS Institute of Information Technology, Lahore, Pakistan.

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: https://doi.org/10.5815/ijmecs.2019.07.02, 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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Using Publications Linked Open Data to Define Organizational Policies

By Muhammad Ahtisham Aslam

DOI: https://doi.org/10.5815/ijieeb.2018.05.02, Pub. Date: 8 Sep. 2018

Researchers around the world are publishing their scientific research results in different forms such as books, journal articles, reference works and project reports. Publishers of these scientific documents usually describe them by using metadata for organizational purposes. This metadata provides a rich information about scientific documents that can be used for analysis purposes such as measuring the impact of researchers and research centers. It can also be used to find scientific documents published in domain of some ones interest, which ultimately can be used to raise the state of the art to the next level. Scientific publications metadata can also be used to analyze the quality and directions of common and highly cited individuals and organizations, and based on this analysis other individuals and organizations can define directions for their future work and research. However, the main limitation of this metadata is that it is available in different formats that might not facilitate the analysis of scientific documents. Therefore, in this paper we clarify that how our SPedia knowledge base (a semantic based knowledge base of scientific publications metadata which we extracted by using SpringerLink as information source) facilitates the analysis of scientific data for policy making. We discuss different kind of questions that can be answered through SPedia knowledge base and we show that how results of these questions can be used to analyze the performance of individuals as well as organizations. We also show that how results of such analysis can help in making organizational policies regarding future research directions.

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