Browsing by Author "Maamar, Zakaria"
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Item A Data-based Guiding Framework for Digital Transformation(CEUR-WS, 2021) Maamar, Zakaria; Cheikhrouhou, Saoussen; Elnaffar, SaidThis paper presents a framework for guiding organizations initiate and sustain digital transformation initiatives. Digital transformation is a long-term journey that an organization embarks on when it decides to question its practices in light of management, operation, and technology challenges. The guiding framework stresses out the importance of data in any digital transformation initiative by suggesting 4 stages referred to as collection, processing, storage, and dissemination. Because digital transformation could impact different areas of an organization for instance, business processes and business models, each stage suggests techniques to expose data. 2 case studies are adopted in the paper to illustrate how the guiding framework is put into action. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).Item Semantic thingsourcing for the Internet of Things(John Wiley and Sons Ltd, 2023-05-15) Maamar, Zakaria; Faci, Noura; Elnaffar, Said; Yahya, Fadwa; Boukadi, Khouloud; Benslimane, DjamalIn the context of Internet of Things, thingsourcing is poised to promote the collective behavior that should prevail among things despite their independent nature being confined into silos. By analogy with crowdsourcing where crowds of (sometimes anonymous) people are contacted for their expertise, thingsourcing abstracts crowds of things and provides the necessary mechanisms for composing things together so they collectively satisfy users' demands. However, to ensure successful discovery of things according to these demands' requirements, an ontology-based semantic description of things is deemed necessary. This article presents an approach for enriching things' descriptions semantically in preparation for their composition with respect to specific scripts that define who will do what, when, and where. A system demonstrating semantic thingsourcing along with a case study about dairy supply-chain is presented in this article as well. © 2021 John Wiley & Sons Ltd.