Nowadays, the ever changing and growing amount of information, regulations, and data requires large organizations to describe on the web increasingly complex and interdependent business processes and services, ideally creating user-profiled content that is clear and up to date. To successfully achieve this goal, as off-the-shelf solutions are missing, institutions have to embark in a digital transformation process fully endorsed by governance, led by a multidisciplinary team of experts, and strongly integrated with artificial intelligence (AI) tools. In this paper we describe how a content service platform, that integrates human processes and state-of-the-art AI services, was successfully employed in our institution (UniGe) to manage, and support a system of about 200 websites. Following a single-sourcing paradigm, its advent allowed for the decoupling of content and technology, preparing UniGe for the future needs of the semantic web.

AI-based component management system for structured content creation, annotation, and publication

Barla, Annalisa;Cuneo, Marina;Nunzi, Simone Roberto;Paniati, Giorgia;Vian, Andrea
2022

Abstract

Nowadays, the ever changing and growing amount of information, regulations, and data requires large organizations to describe on the web increasingly complex and interdependent business processes and services, ideally creating user-profiled content that is clear and up to date. To successfully achieve this goal, as off-the-shelf solutions are missing, institutions have to embark in a digital transformation process fully endorsed by governance, led by a multidisciplinary team of experts, and strongly integrated with artificial intelligence (AI) tools. In this paper we describe how a content service platform, that integrates human processes and state-of-the-art AI services, was successfully employed in our institution (UniGe) to manage, and support a system of about 200 websites. Following a single-sourcing paradigm, its advent allowed for the decoupling of content and technology, preparing UniGe for the future needs of the semantic web.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/1081263
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