- - - December 2026 (workshop day yet to be defined) - - - FULL ONLINE - - -
Co-located with the 2026 IEEE International Conference on Big Data (IEEE Big Data 2026)
Phoenix, AZ, USA, Dec. 14-17, 2026
All accepted papers are expected to receive a waiver on the registration fee,
More details to come!
In the current rapidly evolving technological landscape, Data Spaces and Digital Twins represent two pivotal and transformative data-driven elements whose integration discloses novel opportunities for multiple stakeholders. Data Spaces (DS) are virtual and secure ecosystems designed for managing and aggregating heterogeneous real-time and historical data sources, with the aim of enabling more efficient data sovereignty policies and more interoperable data exchange. Digital Twins (DT) are virtual replicas that allow simulating and analysing the behaviour of a complex physical asset or system under different conditions, both in real time and off-line.
DT have proven to be especially helpful in supporting the decision-making process of cities, industries, and corporations by enabling operators to identify potential issues and optimise system performance without disrupting the services provided to the public. This is particularly relevant in: a) Critical Entities (CE), which are resources and infrastructures providing essential services for maintaining vital societal functions and economic activities (e.g., transportation, energy, or water infrastructures), and b) Smart Urban Communities, which leverage smart technologies to benefit stakeholders and citizens of an interconnected city. In both these cases, the role of data is pivotal, since the accuracy and usefulness of DT strongly depend on data availability and data quality in order to achieve a true digital resilience of critical infrastructures.
The relevance of a proper integration between DT and DS is also confirmed by a series of recent initiatives aimed at proposing dedicated architectures (e.g., International Data Spaces, IDS), collaborative data sharing environments (e.g., European data strategy), and architectural standards (e.g., Gaia-X) in order to enable trusted data exchange in accordance with European data protection guidelines.
The enabling role of DS is rapidly gaining momentum in contexts where centralised cloud-based data storage solutions have to be integrated with highly-distributed edge data processing. Furthermore, data sovereignty requirements in DS for DT 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 CE usually needs 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. Similarly, the European Data Space for Smart Communities (DS4SSCC-DEP) initiative promotes a federated deployment pattern for large-scale DSs aligned with Europe’s Digital Decade objectives [6]. Consequently, high-quality DS are needed to integrate and manage extremely variegated data sources, to allow data-interoperability among multiple systems and organisations, and to support data intensive processing and analytics, specifically focusing on scalability, privacy, and security requirements.
This workshop, now in its third year at the IEEE Big Data flagship conference in the big data sector, aims to bring together researchers and practitioners from computer science and data science domain and from the industry sector and from governmental bodies. The workshop represents 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 data spaces 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 data spaces for DTs.
We invite submissions of original research papers, position papers, and case studies on topics related both to data spaces and digital twins for critical entities and smart urban communities, which include, but are not limited to:
Data spaces supporting big data processing and analytics
Data models and data pipelines
Data integration and interoperability
Data quality assessment and improvement
Data privacy and security
Data provenance, lineage, and sovereignty
Societal impact of data spaces for smart urban communities
Technological enablers of data space ecosystems
Crowd-sourced data and citizen science for smart urban communities
Applications of DT for critical entities and smart urban communities explicitly using data spaces
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 data spaces 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 2026 is required for at least one of the authors for participating in the workshop.
Registration details and fees will be made available soon on the IEEE Big Data 2026.
Oct 15, 2026: due date for full workshop paper submission
Nov 5, 2026: notification of paper acceptance to authors
Nov 20, 2026: camera-ready of accepted papers and registration
Dec 14-17, 2026: workshop
(FULL ONLINE, final date yet to be defined)
== To be yet announced ==
The workshop will be held as an online meeting via the Zoom platform.
Registered authors will receive all the instructions about how to join.
Workshop Chairs
Antonella Longo, Ph.D., M.Sc., IEEE Member
Associate Professor of Database and Information Processing Systems
DataLab, Dept. of Engineering for Innovation
University of Salento, Lecce (Italy)
ORCID: 0000-0002-6902-0160
Marco Zappatore, Ph.D., M.Sc., IEEE Senior Member
Associate Professor in Database and Information Processing Systems
DataLab, Dept. of Engineering for Innovation
& Department of Experimental Medicine
University of Salento, Lecce (Italy)
ORCID: 0000-0002-8277-9390
Alessandra Somma, Ph.D., M.Sc.,
Assistant Professor of Database and Information Processing Systems
Department of Information Technologies and Electrical Engineering, University of Naples Federico II, Naples (Italy)
ORCID: 0000-0001-5372-4588
Program Committee
Alessandra De Benedictis, University of Naples Federico II
Alessandro Lazari, F24
Ali Aghazadeh Ardebili, University of Trento, DIPSCO, CogNosco Lab
Anders Logg, Chalmers University of Technology
Chiara Rucco, University of Salento
Cristian Martella, University of Salento
Dessislava Petrova-Antonova, Sofia University
Fernando López Aguilar, FIWARE Foundation
Francesca Miccoli, University of Salento
Francesca Zampino, University of Salento
Nishu Gupta, University of Fribourg
Stefano De Panfilis, FIWARE Foundation
Tejaswani Dash, Capital Group
Tobia Martina, University of Salento
Vasilis Naserentin, Chalmers University of Technology
Viktoriya Degeler, University of Amsterdam