Title: Data openness for efficient e-governance in the age of big data

Authors: Safae Sossi Alaoui; Yousef Farhaoui; Brahim Aksasse

Addresses: ASIA Team, M2I Laboratory, Department of Computer Science, Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, BP 509 Boutalamine, 52000 Errachidia, Morocco ' ASIA Team, M2I Laboratory, Department of Computer Science, Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, BP 509 Boutalamine, 52000 Errachidia, Morocco ' ASIA Team, M2I Laboratory, Department of Computer Science, Faculty of Sciences and Techniques, Moulay Ismail University of Meknes, BP 509 Boutalamine, 52000 Errachidia, Morocco

Abstract: The data revolution in recent years has led governments around the world to realise the different benefits of communicating and opening data over their information and communication technologies (ICTs) in behalf of their citizens. Indeed, the need for data openness is vitally important for governments, research community and businesses, especially in the era of big data, which characterised by the increase in volume of structured and unstructured data, the speed at which data is generated and collected and the variety of data sources; this is known as the three Vs. Therefore, big data has changed the ways governments manage and support their policies towards their digital data and tend to make it more open and accessible. This 'open data' movement has been adopted by several countries thanks to its multiple benefits in different domains to uncover hidden patterns and improve e-governance effectiveness in terms of cost, productivity and innovation. Through using machine learning algorithms, this paper demonstrates that governments applying open policies are the same as those who get a high score in terms of Human Development Index. To fulfil paper's objectives, the powerful statistical tool named 'IBM SPSS Statistics' is used to accomplish the entire analytical process.

Keywords: open data; e-governance; big data; regression algorithms.

DOI: 10.1504/IJCC.2021.10044184

International Journal of Cloud Computing, 2021 Vol.10 No.5/6, pp.522 - 532

Received: 30 Dec 2019
Accepted: 01 Mar 2020

Published online: 10 Jan 2022 *

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