Toward Building a Linked Open Data Cloud to Predict and Regulate Social Relations in the Saudi Society

 Background: The trend in producing linked open data to publish high-quality interlinked data has gained widespread traction in recent years. Various sectors are producing linked open data to increase public access and ensure transparency, in addition to a better utilization of government data, namely linked open government data. Problem Definition: As compared to the developed countries, Saudi Arabia lags behind in benefiting from this new era of ubiquitous web of data, despite its publication of government related data in non-linked format. In the context of Saudi open government data, the full potential of multi-category data published by various government agencies at different portals is not being realized as the data are not published in open data format and remain unlinked to other existing datasets. Methodology: To bridge this gap, this study presents a framework to extract and generate semantically enriched data from various data sources under different domains. The framework was used to produce the Saudi linked open government data cloud by interlinking data entities with each other and with external existing open datasets. Results: The effectiveness of our approach is validated by applying it to a socially significant issue, i.e., divorce rate, in Saudi Arabia. By posing smart queries to semantically enriched data, we were able to perform an in-depth analysis of different factors related to increasing divorce rates in Saudi Arabia. Arguably, without using linked open data and related technologies such analysis would not have been possible. Finally, we also present a simulated visual environment for better understanding and communication of such analysis for decision and policy makers.