A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia

Abstract

Due to the wide-ranging development of data-oriented sustainable systems in the government and the public sectors, the development of such sustainable systems is replete with potential. The ultimate focus of developing these sustainable systems is to provide citizens with transparency, accountability, awareness as well as a single point of query for asking integrated and smart queries. In view of these benefits, the Saudi government has taken the initiative to publish and develop sustainable open data-oriented information systems. However some major challenges in the Saudi Government Open Data are that the (1) data are published and available in different formats such as Excel sheets, CSV files (Comma Separated Values), images, scanned documents and social media sources such as Twitter, (2) datasets from different government departments are not linked with each other or to existing datasets in Linked Open Data Cloud (even though they have strong links with each other), and (3) there is no SPARQL Endpoint that can be used to pose smart semantic-based queries to Saudi Government Data. This paper is part of an ongoing research project to present a framework that can be used to transfer the government data from different sources to RDF format. The framework can also be used to clean and classify/map the data according to the Saudi Government Ontology. We also describe our approach for semiautomatically linking Saudi Government Datasets with one another as well as with other existing open datasets, thus resulting in the Saudi Linked Open Government Data Cloud (SLOGDC). Finally, taking the topic “Public’s Response to Women’s Driving in Saudi Arabia” as a case study, we demonstrate the SLOGD SPARQL Endpoint as a data-oriented system by executing different queries and analyzing results of these queries. This work also contributes new insights into women’s driving in Saudi Arabia using the SLOGDC, thus suggesting the way forward in shaping policies for decision-making.

Smart City Ontologies and Their Applications: A Systematic Literature Review

“…Recent works in this sectors address the problems of realization of open government data [129], such as linked open data portals, as a single point of access to open government datasets, to provide valuable means to fostering innovation, improving transparency and collaboration by promoting citizens e-participation [130]. Open city platforms for real time monitoring [131] constitute one type of service enabled by linked open data initiatives.…”

“…The Saudi Linked Open Government Data Ontology (SLOGDO) [129] is defined to provide access to public administration datasets to the purpose of transparency. They are: General Authority for Statistics, Ministry of Human Resource and Social Development, Ministry of Interior, Ministry of Civil Service, Ministry of Justice, and Twitter datasets.…”

LOPDF: a framework for extracting and producing open data of scientific documents for smart digital libraries

“…The LOPDF framework algorithm has been enhanced and improved sufficiently for better processing and linking of data items. We also customized this framework to produce the local LOD cloud by extracting and linking data in different domains such as government (AlSukhayri et al, 2020) and education (Alrehaili et al, 2014).…”

Research on Transparent Access Technology of Government Big Data

“…However, challenges still exist in terms of open and transparent access to government data, such as data silos. Therefore, researching the technology for transparent access to government big data can effectively promote modernization in government governance, enhance public participation and innovation capability, and drive social progress and economic prosperity [2].…”

“…Consequently, it is challenging to achieve transparent access to heterogeneous government big data through simple data aggregation methods [24]. (2) Each level of government data management departments has personalized requirements for data reading speed, capacity, and maintenance costs. Meeting the needs of various management users and ensuring dynamic customized data allocation with limited data resources is exceedingly difficult.…”