Towards understanding and harnessing the potential of Africa in digitalization

Nowadays, the digital transformation is an intensive subject that refers to all the changes related to a process with the integration of advanced digital technologies such as cloud computing, Internet of Things, three-dimensional printing, artificial intelligence, and transportation in all aspects of human society. Digitalization affects any firm, any sector, any type of job, any function in organizations/institutions. Then it has become ubiquitous in multiple domains such as oil and gas, disease management, finance, banking, transportation, education, healthcare, agriculture, energy, environment, gastronomy, government services, and so forth. Africa is the world’s second-largest and second-most-populous continent. Despite a wide range of natural resources, the continent suffers from many problems such as poverty, diseases, illiteracy, weak infrastructure, political instability, and conflicts. The continent features a relatively young population, as well as a diaspora of expatriate African researchers all willing to contribute to its development. Digital communication has spread very fast with improved access to the Internet. All these must enable an African shift to a successful digitalization transformation story with the promotion of technological advancements. The promotion of high education and research in Africa is one of the important keys for achieving digital transformation. This special issue has been launched by five researchers: four from African countries: Algeria, Morocco, Senegal, and Tunisia, and one from the African diaspora, working in France. This issue is dedicated to African young researchers contributing to digitalization efforts. An open call for papers has been organized, where it attracted 25 papers covering topics related to digitalization transformation, more particularly big data analytics, data integration, data mining, social media data exploitation, decision support systems, cloud computing, smart applications, Internet of Things, data security and risk, web services, quality of data transmission, recommendation, and combinatorial optimization methods. All submissions were peer-reviewed by at least two reviewers from our international program committee consisting of academia and industrials from 12 different countries and working on the various topics of our special issues. After two rounds of reviews, we finally accepted 11 papers, making an acceptance rate of 44%. One of the interesting characteristics of our accepted papers is that some of them integrate real case studies involving important domains in Africa such as Algerian mobile telecommunication and transportation services in the Maghreb countries. We congratulate the authors who submitted articles to our special issue. The 11 selected papers are summarized as follows: The first paper, entitled “A RoadSide Unit Deployment Framework for Enhancing Transportation Services in Maghrebian Cities” by Chaabene et al.1 addresses the problem of roadside units (RSUs) deployment in Maghribian cities. Solving this problem contributes to providing Intelligent Transportation Systems. The authors introduce a new spatio-temporal RSU deployment framework composed of three methods: SPaCov, SPaCov+, and HeSPIC. These methods aim at mining mobility patterns extracted from vehicle trajectories to improve the coverage ratio of the framework. Therefore, they propose efficient coverage algorithms to compute the appropriate RSUs locations that cover all the extracted mobility patterns. To evaluate the efficiency and effectiveness of the proposed methods, an empirical study has been conducted considering different simulation scenarios. This study includes real datasets of trajectories representing three portions of urban areas in Algeria and Tunisia. These methods were compared against the minimal mobility patterns coverage method using specific metrics such as coverage ratio, deployment cost, network latency, and overhead. The second paper, entitled “Graph-based tag recommendations using clusters of patients in Clinical Decision Support System” by Hafidi et al.2 is concentrated on the important problem of tag recommendation for enhancing clinical decision support systems to extract similar patient’s pathologies. The authors provide an interesting state-of-art covering Tag recommendation and Community detection. After that, they propose a graph-based tag recommendation approach that suggests relevant tags (diseases and pathologies) by analyzing the tagged medical images. This approach uses graph analytics to generate tags, patients, and image graphs. The proposed solution is evaluated using the dataset ChestX-Ray14. The obtained results are encouraging in assisting doctors in day-to-day tasks. The third paper, entitled “Opinion Leaders Detection in Dynamic Social Networks Communities” by Oueslati et al.3 deals with the problem of detecting influential users in dynamic social network communities. This problem is quite important in various domains such as politics, health care, raising awareness on important issues, advertising and marketing, and so forth. To deal with this problem, the authors propose a detection approach,