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Data spaces and digital twins: models and technologies

Data spaces and digital twins: models and technologies

Marco Zappatore, Angelo Martella, Antonella Longo
10 July 2024
VIDEO

Abstract

A digital twin (DT) is a virtual representation of a physical object, system, or process (including cities, and even ecosystems), synchronised with the real-world entity it replicates. Internet of Things (IoT) technologies, such as sensors and actuators, big data, AI, cyberscuirty are enabling technologies of this novel paradigm. A DT can be used to experiment, simulate, analyse, adapt, and optimise the behaviour, performance and maintenance of the real-world counterpart, including its interaction with other objects or systems. DTs enable interoperable exchange between participants by defining a subset of suitable data formats and integrating data models, plus a set of other features related to data severaignity, interoperability and security, as in the definition of dataspace. The webinar will introduce the concept of EU dataspace and how they can be implemented in the Digital twins scenario.

Speakers

  • Marco Zappatore
    University of Salento

    (M.Sc. Telecommunications Engineering 2008, Ph.D. Information Engineering, 2012) is currently a senior researcher in database and information systems at the Department of Engineering for Innovation at the University of Salento (Lecce, Italy). His research interests include data and knowledge management, mobile crowd sensing and citizen science, novel technological approaches and didactic paradigms for STEM education. He has co-authored more than 100 Scopus-indexed papers on international journals and conferences. He is IEEE Senior Member (IEEE Computer Society; Education Society), Associate Editor for IEEE Transactions on Learning Technologies (TLT), reviewer for several international scientific journals on data management and STEM education, as well as TPC member of several international conferences on computer science, big data technologies, e-education, and cloud-learning.

  • Angelo Martella
    University of Salento

    PhD, Eng. Angelo Martella is a junior researcher at the DataLab of the University of Salento. He is currently an academic teacher in Big Data Management and Data Science and Engineering at the same department. The research topics ihe is involved in are related to the development of the Digital Twins paradigm and Data Space concept. Consequently, his areas of expertise encompass all stages of the design, development, and implementation of digital twins for smart cities, with an emphasis on adopting data spaces as essential facilitators of the resulting data ecosystem by managing data flows in distributed edge-cloud environments.

  • Antonella Longo
    University of Salento
    HOMEPAGE

    Antonella Longo, is associate professor at the Department of Engineering for Innovation of the University of Salento, received the PhD in Information Engineering in 2004. She teaches Database, Data Management , Big data Management, data engineering and security of critical infrastructures at Computer Engineering, Management Engineering and Engineering for the security of Critical Infrastructruters (bach and Ms.C. classes). Her research interests include information systems and databases, service-oriented architectures design for cloud and edge infrastructure, and tools for enhancing citizen science. Her current research focuses on models and tools for big data management and the exploration of edge/cloud architecture in cyber-physical systems. She has published more than 100 papers on these topics in peer-reviewed journals and international conference proceedings. She is the coordinator of DataLab (datalab.unisalento.it), the data lab at University of Salento and the DidaLab (didalab.unisalento.it), the lab about innovative model in education based on digital tools. She is also Associate Editor of the IEEE Journal of Internet of Things and of Taylor’s Software and Practice. She is also a member of the Scientific Advisory board of Fiware Foundation.