The 2nd International Workshop on Smart AI Models & Data Sharing and Monetisation.
About SmartAIDa
The 2nd International Workshop on Smart AI Models and Data Sharing and Monetisation (SmartAIDa) aims
to address the growing need for effective frameworks and technologies that enable the sharing,
monetisation, and governance of AI models and datasets. As artificial intelligence becomes a cornerstone of
innovation across industries, leveraging its full potential requires robust infrastructures, interoperability, and
a focus on trust, security, and value creation.
The Workshop focuses on:
AI Model and Dataset Sharing: Developing frameworks, platforms, and tools to facilitate secure,
ethical, and interoperable sharing of AI models and datasets.
Data Monetisation: Strategies for deriving economic value from datasets and AI models while
ensuring compliance with data governance standards.
Trust and Governance: Addressing trust, accountability, and ethical challenges in data-sharing
ecosystems.
Technology Infrastructure: Leveraging cutting-edge technologies such as blockchain, edge
computing, and IoT to support secure AI model sharing and data exchange.
Applications and Use Cases: Exploring practical implementations in areas like healthcare,
transportation, and finance.
SmartAIDa workshop is under the umbrella of IEEE SMARTCOMP 2026 (Messina, Italy, 22–25 June 2026).
The workshop invites high-quality submissions addressing the challenges, opportunities, and innovations in
sharing AI models and datasets and maximising the value derived from data through monetisation and trust
frameworks.
We welcome original contributions that include, but are not limited to:
AI model and dataset sharing
Standards and protocols for AI model interoperability.
Platforms and tools for dataset and model sharing in decentralised environments.
Ownership, attribution, and IP management for shared AI assets.
Technical and ethical challenges in model reuse and adaptation.
Valuation models for datasets and AI models based on quality and usage.
Incentive mechanisms for encouraging data and model sharing.
Use cases demonstrating successful data and model monetisation strategies.
Privacy-preserving techniques for shared data and models (e.g., differential privacy, homomorphic
encryption).
Ensuring fairness and reducing bias in shared datasets and models.
Role of cloud, edge, and IoT systems in AI sharing ecosystems.
Applications of shared AI models in healthcare, transportation, finance, and other domains.
Case studies demonstrating the economic impact of shared data and models.
Practical challenges and solutions in deploying shared AI systems in production environments.
Economic and policy perspectives on data sharing and AI model monetisation.
Legal frameworks and regulations impacting AI model sharing.
Interdisciplinary approaches to addressing technical, ethical, and economic challenges.
For Authors
Authors are invited to submit original and unpublished research papers to the SmartAIDa workshop.
Submissions should present novel contributions and should not be under consideration for publication in any other conference or journal.
The workshop seeks state-of-the-art research and advancements in the area of Smart AI Models & Data Sharing and Monetisation.
Important Days
Paper submission deadline: March 9, 2026
Notification of acceptance: April 29, 2026
Camera-ready deadline: Early May 2026 (main conference deadline expected to be extended)
Template and Format
Paper submissions should be no longer than 6 pages (10pt font, 2-column format), including text, figures, and tables using the IEEE conference template.
Submission
Papers must be submitted electronically as PDF files through the SMARTCOMP 2026 workshop submission system (link to be announced).
If you do not have an EDAS account, please, register.
Authors of invited papers must submit their paper(s) using the EDAS dedicated online submission application.
All submitted papers will be subject to single blind peer reviews by Technical Program Committee members.
For the accepted papers to be included in the proceedings, the camera-ready version must be submitted using the recommended format. Maximum workshop paper lenght is 6 pages and no extra page is allowed.
The final PDF has to conform to the requirements for publishing on IEEE Xplore. The submission link will take you to the verification tools provided by IEEE.
Publication
All accepted papers presented in the workshop will be published in the proceedings of the conference and published in the IEEE Xplore Digital Library and Scopus indexed.
Registration
Each accepted workshop paper requires a full SMARTCOMP registration (registration for workshops only is not available)Accepted papers must be presented in person by at least one author with a corresponding full registration. Failure to comply with this requirement will result in the exclusion of the paper from the final proceedings, the conference program, and from the IEEE Digital Library.
Keynote Speaker (To Be Confirmed)
Committees
The event is organised by a dedicated committee of experts and professionals in the field. The organisers are committed to fostering collaboration, sharing insights, and driving innovation, supported by an international Program Committee.
The detailed workshop programme will be published after paper acceptance.
Venue
The workshop will take place in conjunction with IEEE SMARTCOMP 2026 at: Department of Engineering, University of Messina
Messina, Italy
Organisers & Partners
Dr Andrea Visentin
Dr Andrea Visentin
Associate Professor
University College Cork
Dr Andrea Visentin is an Associate Professor and the PhD Programme Director at the School of Computer Science & IT at University College Cork (Ireland). He holds a BSc and an MSc in Computer Engineering from the University of Padua (Italy) and completed a PhD at the Insight Centre for Data Analytics. His research focuses on optimisation, artificial intelligence, and their combination. In optimisation, the main emphasis is on stochastic inventory control and lot sizing. In AI, his work involves applications in Boolean satisfiability, time series forecasting, infrastructure health prediction devices, and medical biophotonics. He is a Funded Investigator at the RI Insight Centre for Data Analytics, a Principal Investigator for the DATAMITE Horizon Europe project, and part of the RI Centre for Research Training in AI, and the Tyndall National Institute.
Dr Martin Serrano
Dr Martin Serrano
Senior Research Fellow
University of Galway
Dr Martin Serrano is a recognised expert on semantic interoperability and distributed systems due to his scientific contribution(s) using liked data and semantic formalisms like ontology web language for the Internet of Things and federated data mechanisms to store and manage the collected sensor’s data in the Cloud. He has also contributed to define the data interplay in edge computing using the linked data paradigm; in those works, he has received awards recognizing his scientific contributions and publications. Dr Serrano has advanced the state of the art on pervasive computing using semantic data modelling and context awareness methods to extend the "autonomics" paradigm for networking systems. He has also contributed to the area of information and knowledge engineering using semantic annotation and ontologies for describing data and services relations in the computing continuum. Dr Serrano has defined the data continuum and published several articles on data science and Internet of Things science and he is a pioneer and visionary on proposing that semantic technologies applied to data management systems can be used as an approach to produce cognitive applications capable of understanding, service and produce application events, completing the services life cycle and thus enabling full-stack control loops. A process called bringing semantics into the box, as published in one of his academic books. He has published 5 academic books, 6 research books and more than 100 peer reviewed articles in IEEE, ACM and Springer conferences and journals
Prof. Edward Curry
Prof. Edward Curry
Established Professor of Data Science
University of Galway
Prof. Edward Curry is the Established Professor of Data Science and Director of the Insight SFI Research Centre for Data Analytics and Data Science Institute at the University of Galway. Edward has made substantial contributions to semantic technologies, incremental data management, event processing middleware, software engineering, as well as distributed systems and information systems. He combines strong theoretical results with high-impact practical applications. The excellence and impact of his research have been acknowledged by numerous awards, including best paper awards and the University of Galway Presidents Award for Societal Impact in 2017. His team's technology enables intelligent systems for smart environments in collaboration with several industrial partners. He is organiser and programme co-chair of major international conferences, including CIKM 2020, ECML 2018, IEEE Big Data Congress, and European Big Data Value Forum. Edward is co-founder and elected Vice President of the Big Data Value Association (BDVA) and the AI, Data and Robotics Association (Adra). He has built consensus on a joint European research and innovation agendas and influenced European data and AI innovation policy to deliver on the agendas. He is a member of the Data Architecture amp; Technical Committee of the Irish Government Data Governance Board.
