SEcure Decentralised Intelligent Data MARKetplace

Informazioni relative al progetto

SEDIMARK

ID dell’accordo di sovvenzione: 101070074

DOI

10.3030/101070074

Progetto chiuso

Data della firma CE 15 Giugno 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2025

Finanziato da

• Digital, Industry and Space

Costo totale

€ 5 250 985,00

Contributo UE

€ 4 396 835,50

Coordinato da

ATOS IT SOLUTIONS AND SERVICES IBERIA SL
Spain

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (7)

SEDIMARK architecture and interfaces. First version

Intermediate specification of the SEDIMARK architecture and interfaces, including updated requirements

Use cases definition and initial requirement analysis

This report will provide the initial detailed description of the project use cases and the initial requirements.

Dissemination and exploitation plan

Main plan for the dissemination, exploitation and communication activities

Edge data processing and service certification. First version

Report on tools and processes for enabling data processing and sharing in an interoperable way at the data sources. First version

Decentralized infrastructure and access management. First version

Definition of the decentralised infrastructure and the identity and access management techniques, output of T3.1 and T3.3. First version

Evaluation methodology, metrics and integration plan

Definition of the plan for integration and evaluation of SEDIMARK and the metrics used for testing.

Dissemination and Impact creation activities. First version

Dissemination, exploitation and communication activities to be updated. Report on the project activities for dissemination, communication and cooperation with other initiatives: First version

Demonstrators, pilots, prototypes (4)

Integrated releases of the SEDIMARK platform. First version

Report and software for the integrated platform. First version

Energy efficient AI-based toolset for improving data quality. First version

Report and code for the output of Tasks 3.1 and 3.5, detailing the techniques for improving data quality in an energy efficient way. First version

Enabling tools for data interoperability, distributed data storage and training distributed AI models. First version

Report/code for the outputs of Tasks 3.2, 3.3 and 3.4, detailing the models for ensuring data interoperability, distributed storage of data and how they are used for training distributed AI models. First version.

Data sharing platform and incentives. First version

Report and code for the services of the data sharing platform, including incentives for ethical sharing. First version

Data Management Plan (2)

Data Management Action Plan. First version

This deliverable will detail the implementation of the Open Research Data policy of the EC in HE. First version

Data Management Action Plan. Second version

This deliverable will detail the implementation of the Open Research Data policy of the EC in HE. Second version

Websites, patent fillings, videos etc. (1)

Project website and dissemination material

The project website will be online and dissemination material (i.e. leaflets, brochures) will be designed.

Pubblicazioni

Book chapters (3)

Entity Matching with Large Language Models as Weak and Strong Labellers

Autori: Diarmuid O’Reilly-Morgan, Elias Tragos, Erika Duriakova, Honghui Du, Neil Hurley, Aonghus Lawlor
Pubblicato in: Communications in Computer and Information Science, New Trends in Database and Information Systems, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70421-5_6

Leveraging Edge Analytics for Enhanced Data Quality in IoT Systems

Autori: Marianne MAROT, Gilles ORAZI, Luis SANCHEZ, Laura MARTIN, Diarmuid O’REILLY-MORGAN, Erika DURIAKOVA, Elias TRAGOS, Franck LE GALL
Pubblicato in: Springer Handbook for Data Engineering, Numero 1, 2024, ISSN 2522-8692
Editore: Springer

DiffGR: A Discrete Diffusion-Based Model for Personalised Recommendation by Reconstructing User-Item Bipartite Graphs

Autori: Zheng Ju, Honghui Du, Elias Tragos, Neil Hurley, Aonghus Lawlor
Pubblicato in: Lecture Notes in Computer Science, Advances in Information Retrieval, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-88714-7_23

Other (1)

A decentralised architecture for secure exchange of assets in data spaces: The case of SEDIMARK

Autori: Duriakova, Erika; O'Reilly-Morgan, Diarmuid; Bahri, Maroau; Costalonga, Maxime; Danciu, Gabriel; Nechofor, Septimiu; Jarcau, Stefan-Cristian; Elsaleh, Tarek; Wu, Peipei; Le Gall, Franck; Koutantos, Grigorios; Vlacheas, Panagiotis; Sánchez González, Luis; Santana Martínez, Juan Ramón; Sotres García, Pablo; Tragos, Elias Z.
Pubblicato in: Data in Brief, 2025
Editore: Springer
DOI: 10.1016/J.DIB.2025.111757

Peer reviewed articles (3)

On the Need of International Cross-Data Space Interworking: An EU–Japan Case Study

Autori: Juan Ramón Santana, Luis Sánchez, Martin Bauer, Benjamin Hebgen, Ernö Kovacs, Satsuki Hamaguchi, Yuriko Nomura
Pubblicato in: IT Professional, Numero 27, 2025, ISSN 1520-9202
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/MITP.2025.3545214

Contemporary development directions for urban digital twins

Autori: Juho-Pekka Virtanen, Jukka Alander, Heli Ponto, Ville Santala, Renske Martijnse-Hartikka, Andreas Andra, Timo Sillander
Pubblicato in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Numero XLVIII-4/W10-2024, 2024, ISSN 2194-9034
Editore: Copernicus GmbH
DOI: 10.5194/ISPRS-ARCHIVES-XLVIII-4-W10-2024-177-2024

Pneumonia Image Classification Using DenseNet Architecture

Autori: Mihai Bundea, Gabriel Mihail Danciu
Pubblicato in: Information, Numero 15, 2025, ISSN 2078-2489
Editore: MDPI AG
DOI: 10.3390/INFO15100611

Conference proceedings (8)

ASML: A Scalable and Efficient AutoML Solution for Data Streams

Autori: Nilesh Verma, Albert Bifet, Bernhard Pfahringer, Maroua Bahri
Pubblicato in: International Conference on Automated Machine Learning, 2024
Editore: Sorbonne University

Multi-Label Transfer Learning in Non-Stationary Data Streams

Autori: Du, Honghui, Leandro Minku, Aonghus Lawlor, and Huiyu Zhou
Pubblicato in: 2025 IEEE International Conference on Data Mining (ICDM), 2025
Editore: IEEE

Elevating Water Flow Level Predictions through Strategic Feature Elimination

Autori: Iuliana-Andreea Stroia-Vlad, Danciu Gabriel Mihail, Nechifor Cosmin Septimiu
Pubblicato in: 2024 IEEE International Conference And Exposition On Electric And Power Engineering (EPEi), 2024
Editore: IEEE
DOI: 10.1109/EPEI63510.2024.10758054

Exploring Digital Twins for Urban Mobility: Applications and the Case Study of Helsinki

Autori: Guilhermina Torrao, Juho-Pekka Virtanen, Emmi Volanen
Pubblicato in: 2025 International Workshop on Intelligent Systems (IWIS), 2025
Editore: IEEE
DOI: 10.1109/IWIS66215.2025.11142394

NodeRec+: A Lightweight Framework for Federated Recommender Systems

Autori: Diarmuid O'Reilly-Morgan, Erika Duriakova, Elias Tragos, Neil Hurley, Aonghus Lawlor
Pubblicato in: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025
Editore: ACM
DOI: 10.1145/3726302.3730138

Exploring Coresets for Efficient Training and Consistent Evaluation of Recommender Systems

Autori: Zheng Ju, Honghui Du, Elias Tragos, Neil Hurley, Aonghus Lawlor
Pubblicato in: 18th ACM Conference on Recommender Systems, 2025
Editore: ACM
DOI: 10.1145/3640457.3691716

Data Marketplaces for Enhanced Water Management

Autori: Franck Le Gall, Jérôme Grégoire, Jérémy Deremarque, Thomas Bousselin and Iheb Khelifi
Pubblicato in: SimHydro 2025, 2025
Editore: Société Hydrotechnique de France

RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models

Autori: Dairui Liu, Boming Yang, Honghui Du, Derek Greene, Neil Hurley, Aonghus Lawlor, Ruihai Dong, Irene Li
Pubblicato in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2025
Editore: ACM
DOI: 10.1145/3627673.3679987

Monographic books (1)

Elevating Data Quality A Paradigm Shift for Data Spaces and AI Needs

Autori: Daniel Alonso (BDVA), Arturo Medela (EVIDEN), Elias Tragos (UCD), Franck Le Gall (EGM), Gabriel Danciu (Siemens), Luis Sanchez (UC), Maroua Bahri (INRIA), et. Al.
Pubblicato in: 2024
Editore: Big Data Value Association