- - - FULL ONLINE - - -
Co-located with the 2024 IEEE International Conference on Big Data (IEEE Big Data 2024)
Washington, DC (USA), Dec. 15, 2024
All accepted papers have received a full-waiver on the registration fee,
thanks to the sponsoring of the ICSC Foundation (Italian Center of Supercomputing)
Critical Entities (CEs), intended as systems providing essential services for maintaining vital societal functions and economic activities, and smart urban communities, which leverage smart technologies to benefit stakeholders and citizens of an interconnected city, represent nowadays two increasingly growing areas for the application of Digital Twins (DTs), which are virtual replicas that allow to simulate and analyse the behaviour of a complex system under different conditions of physical assets as pivotal as transportation, energy, or water systems, thus supporting their effective management in smart cities, industries, and corporations. DTs are especially helpful in the decision-making process as they enable operators to identify potential issues and optimise system performances without disrupting the services provided to the public, as well as to industrial and business stakeholders. In such a scenario, the role of data is pivotal as the accuracy and usefulness of DTs strongly depend on data availability and data quality in order to achieve a true digital resilience of critical infrastructures.
Therefore, the promising integration with dataspaces, intended as virtual spaces for managing and aggregating heterogeneous real-time and historical data sources, can further enhance effectiveness and applicability of DTs for critical entities. Several current initiatives aimed at proposing dedicated architectures (as the International Data Spaces, IDS), collaborative data sharing environments (as the European data strategy), and architectural standards (as the GAIA-X initiative) enabling trusted data exchange in accordance with European data protection guidelines, are nowadays paving the way to adopt dataspaces as a fundamental building block of truly data-driven DTs for critical entities.
The enabling role of dataspaces is rapidly gaining momentum in situations where centralised cloud-based data storage solutions have to be integrated with highly-distributed edge data processing. Furthermore, data sovereignty requirements in dataspaces for DTs for critical entities constitute another engaging challenge, as it is crucial to ensure that data are secured and protected from unauthorised access, misuse, or deletion, particularly when the right of a country or an organisation to keep the ownership and control over its own data is at stake. This aspect is even more relevant in specific geographical regions, as the recent Critical Entity Resilience Directive (CER) of the European Union asks EU Member States to define national resilience harmonisation strategies and risk assessment frameworks, which would greatly benefit from the adoption of data-driven approaches. Moreover, the data generated by a DT for a critical entity usually need to be shared with other stakeholders, such as national and international regulatory authorities or maintenance contracting companies, and data sovereignty must be ensured without hindering data interoperability, sharing, and usage.
Consequently, high-quality dataspaces capable of integrating and managing extremely variegated data sources, allowing data-interoperability among multiple systems and organisations, and supporting data-intensive processing and analytics are needed, with a specific focus on scalability, privacy, and security requirements.
This workshop, previously known under the acronym of DS4DTCCI and now in its second year at the IEEE Big Data flagship conference in the big data sector, aims to bring together researchers and practitioners not only from computer science and data science but also from the industry sector and from governmental bodies. The workshop will represent a fruitful opportunity for discussing the latest research developments and the ongoing challenges in the field, as well as for fostering collaborations and networking.
Critical Entities (CEs), intended as systems providing essential services for maintaining vital societal functions and economic activities, and smart urban communities, which leverage smart technologies to benefit stakeholders and citizens of an interconnected city, represent nowadays two increasingly growing areas for the application of Digital Twins (DTs), which are virtual replicas that allow to simulate and analyse the behaviour of a complex system under different conditions of physical assets as pivotal as transportation, energy, or water systems, thus supporting their effective management in smart cities, industries, and corporations. DTs are especially helpful in the decision-making process as they enable operators to identify potential issues and optimise system performances without disrupting the services provided to the public, as well as to industrial and business stakeholders. In such a scenario, the role of data is pivotal as the accuracy and usefulness of DTs strongly depend on data availability and data quality in order to achieve a true digital resilience of critical infrastructures.
Therefore, the promising integration with dataspaces, intended as virtual spaces for managing and aggregating heterogeneous real-time and historical data sources, can further enhance effectiveness and applicability of DTs for critical entities. Several current initiatives aimed at proposing dedicated architectures (as the International Data Spaces, IDS), collaborative data sharing environments (as the European data strategy), and architectural standards (as the GAIA-X initiative) enabling trusted data exchange in accordance with European data protection guidelines, are nowadays paving the way to adopt dataspaces as a fundamental building block of truly data-driven DTs for critical entities.
The enabling role of dataspaces is rapidly gaining momentum in situations where centralised cloud-based data storage solutions have to be integrated with highly-distributed edge data processing. Furthermore, data sovereignty requirements in dataspaces for DTs for critical entities constitute another engaging challenge, as it is crucial to ensure that data are secured and protected from unauthorised access, misuse, or deletion, particularly when the right of a country or an organisation to keep the ownership and control over its own data is at stake. This aspect is even more relevant in specific geographical regions, as the recent Critical Entity Resilience Directive (CER) of the European Union asks EU Member States to define national resilience harmonisation strategies and risk assessment frameworks, which would greatly benefit from the adoption of data-driven approaches. Moreover, the data generated by a DT for a critical entity usually need to be shared with other stakeholders, such as national and international regulatory authorities or maintenance contracting companies, and data sovereignty must be ensured without hindering data interoperability, sharing, and usage.
Consequently, high-quality dataspaces capable of integrating and managing extremely variegated data sources, allowing data-interoperability among multiple systems and organisations, and supporting data-intensive processing and analytics are needed, with a specific focus on scalability, privacy, and security requirements.
This workshop, previously known under the acronym of DS4DTCCI and now in its second year at the IEEE Big Data flagship conference in the big data sector, aims to bring together researchers and practitioners not only from computer science and data science but also from the industry sector and from governmental bodies. The workshop will represent a fruitful opportunity for discussing the latest research developments and the ongoing challenges in the field, as well as for fostering collaborations and networking.
This workshop is primarily aimed at researchers and practitioners interested in the design and development of data-driven dataspaces and DTs for critical entities and smart urban communities.
Therefore, we encourage submissions from computer scientists working on data management, analytics, and visualization; data security experts actively involved in protecting DTs; data scientists working on industrial data and Industrial-IoT solutions for critical infrastructures; urban planners actively involved in data-driven urban modelling.
Finally, we also welcome participation from industry representatives, in particular those involved in the operational management of industrial critical entities, who want to present peculiar case studies about dataspaces for DTs.
We invite submissions of original research papers, position papers, and case studies on topics related both to dataspaces and digital twins for critical entities and smart urban communities, which include and are focused on, but are not limited to:
Data integration and interoperability
Data quality assessment and improvement
Data privacy and security in DTCCIs
Data provenance, lineage, and sovereignty
Dataspaces supporting big data processing and analytics
Data models and data pipelines
Crowd-sourced data and citizen science for smart urban communities
Applications of DTs for critical entities and smart urban communities explicitly using dataspaces
Novel datasets supporting the development, testing, and validation of DTs
Data-driven security of DTs for critical entities
Data-driven risk assessment of DT-supported critical entities
Data-driven risk harmonisation of DT-supported critical entities
Data-driven DTs enabling urban planning and monitoring
Software platforms for the development of Dataspaces in DTs
Software platforms enabling the development of data-driven DTs
Authors can submit their papers as well as find paper submission guidelines and templates at this LINK
The workshop accepts both full-length papers (up to 10 pages, references included) and short/position papers (up to 5 pages, references included).
Papers must be formatted according to the IEEE 2-column format (IEEE Computer Society Proceedings Manuscript template). Formatting guidelines can be found here.
Full registration of IEEE Big Data 2024 is required for at least one of the authors for participating in the workshop.
Registration details and fees are detailed on the IEEE Big Data 2024 main website, at this LINK.
Oct 20, 2024 Nov 13, 2024: due date for full workshop paper submission
Nov 16, 2024: notification of paper acceptance to authors
Nov 21, 2024: camera-ready of accepted papers and registration
Dec 15, 2024: workshop (FULL ONLINE)
The workshop will be held as an online meeting via the Zoom platform. Registered authors have already received the instructions about how to join.
Workshop Chairs
Antonella Longo, Ph.D., M.Sc., IEEE Member
Associate Professor of Database and Information Systems
DataLab, Dept. of Engineering for Innovation, Univ. of Salento, Lecce (Italy)
ORCID: 0000-0002-6902-0160
Marco Zappatore, Ph.D., M.Sc., IEEE Senior Member
Senior Researcher in Database and Information Systems
DataLab, Dept. of Engineering for Innovation, Univ. of Salento, Lecce (Italy)
ORCID: 0000-0002-8277-9390
Angelo Martella, Ph.D., M.Sc., IEEE Member
Junior Researcher in Database and Information Systems
DataLab, Dept. of Engineering for Innovation, Univ. of Salento, Lecce (Italy)
ORCID: 0000-0002-1082-7293
Program Committee
Dessislava Petrova-Antonova, Sofia University
Anders Logg, Chalmers University of Technology
Vasilis Naserentin, Chalmers University of Technology
Viktoriya Degeler, University of Amsterdam
Stefano De Panfilis, FIWARE Foundation
Fernando López Aguilar, FIWARE Foundation
Alessandra De Benedictis, University of Naples “Federico II”
Alessandra Somma, University of Naples “Federico II”
Alessandro Lazari, University of Salento, F24
Ali Aghazadeh Ardebili, HSPI, University of Salento
Antonella Calò, University of Salento
Amro Issam Hamed Attia Ramadan, University of Salento
Cristian Martella, University of Salento
Francesca Miccoli, University of Salento