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CORDIS - Resultados de investigaciones de la UE
CORDIS

Energy-efficient AI-ready Data Spaces

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Stakeholder Engagement and Dissemination Plan (se abrirá en una nueva ventana)

Document registering the key activities per target group, pertaining to maximizing the dissemination of GREEN.DAT.AI outcomes during and after the project’s lifecycle.

Pilots' Scoping Document (se abrirá en una nueva ventana)

Report outlining the demonstrators’ implementation plans, milestones. The report will identify key stakeholders for the testing/validation phase and include the User Acceptance test templates.

Use Case Requirements, KPIs & Reference Architecture (se abrirá en una nueva ventana)

Report consolidating results of work carries out in WP1 tasks T1.1 - T1.4. More specifically, it sets out the business & technical requirements, specifies the overall solution architecture based on the outputs of the activities in T1.2 and T1.3, and lays out the testing framework for all the pilots.

First Version of Energy-Efficient Large-Scale Data Analytics Services (se abrirá en una nueva ventana)

D3.1 presents the first iteration of the work employed towards the design and development of nine different services that aspire to provide energy-efficient large-scale data analytics. The software library and report will cover AI-enabled data enrichment, Incentive mechanisms for Data Sharing, Synthetic Data Generation, Large-scale learning at the Edge/Fog, Federated & Auto ML at the edge/fog, Explainable AI, Feature Learning with Privacy Preservation, Federated & Automatic Transfer Learning, Adaptive FL for Digital Twin Applications, Automated IoT event-based change detection/ forecasting.

Data Management infrastructure and tools to support Dynamic Ecosystems (se abrirá en una nueva ventana)

D2.1 showcases the design and development of the BDA infrastructure including the Federated Data Sovereignty services and the plan for data pipelines management and continuous integration. It also delivers the visualisation tools needed for the pilots, the workflow management engine required to schedule distributed analytics pipelines, and, finally, wrappers that secure computations & sensitive data at the edge/fog/cloud. A report will detail or the platform components, their interfaces, and data pipelines management mechanisms. The deliverable will include the first prototype of the visualisation workbench, interfaces, distributed analytics services, workflow management engine, and the wrappers for Securing Computations and Sensitive Data at the Edge/Fog/Cloud.

Publicaciones

GREEN.DAT.AI: an energy-efficient, AI-ready data space

Autores: Ben Capper
Publicado en: Red Hat Research Quarterly (Q3 25), 2025
Editor: Red Hat Research

AI-ready Data Products

Autores: Pezuela Robles, C. M., De Majo, C., Alonso, D., Curry, E., Simperl, E., Laatikainen, G., Fidan, G., Chrysakis, I., Giner Miguelez, J., Aas, K., Majithia, N., Plebani, P., & Carey-Wilson, T. (2025, December). AI-ready data products. Big Data Value Associat
Publicado en: BDVA Publications, 2025
Editor: BDVA

Connecting Data Spaces, a practical approach using the Sovity Connector (se abrirá en una nueva ventana)

Autores: Panos Protopapas, Despina Brasinika, Ioanna Fergadiotou, Yaroslav Yavornytskyi, Martin Wagner, Arturo Medela
Publicado en: 2025
Editor: Zenodo
DOI: 10.5281/ZENODO.18030959

GREEN.DAT.AI: Enabling energy-efficient AI services

Autores: Ioanna Fergadioou
Editor: Innovation News Network

Fingerprinting the Shadows: Unmasking Malicious Servers with Machine Learning-Powered TLS Analysis (se abrirá en una nueva ventana)

Autores: Andreas Theofanous, Eva Papadogiannaki, Alexander Shevtsov, Sotiris Ioannidis
Publicado en: Proceedings of the ACM Web Conference 2024, 2024
Editor: ACM
DOI: 10.1145/3589334.3645719

Dataset2Graph: A GNN-based Methodology for AutoML for Clustering

Autores: E. Dilmperis, Y. Poulakis, D. Petratos, C. Doulkeridis
Publicado en: 9th Workshop of Data Management for End-to-End Machine Learning (DEEM’25)
Editor: DEEM

Geolet: An Interpretable Model for Trajectory Classification (se abrirá en una nueva ventana)

Autores: Cristiano Landi, Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni
Publicado en: Lecture Notes in Computer Science, Advances in Intelligent Data Analysis XXI, 2024
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-031-30047-9_19

An AutoML Approach for Bike Demand Forecasting and Redistribution (se abrirá en una nueva ventana)

Autores: Dimitris Petratos, Yannis Poulakis, Irene Gimenez Pedralba, Cristina Aragon Garcia, Christos Doulkeridis
Publicado en: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Intelligent Transport Systems, 2025
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-031-86370-7_9

Pythia: Distributed Pattern-based Future Location Prediction of Moving Objects

Autores: Panagiotis Tampakis, Nikos Pelekis
Publicado en: ISSN 1613-0073
Editor: CEUR Workshop Proceedings (CEUR-WS.org)

Interpretable Data Partitioning Through Tree-Based Clustering Methods (se abrirá en una nueva ventana)

Autores: Riccardo Guidotti, Cristiano Landi, Andrea Beretta, Daniele Fadda, Mirco Nanni
Publicado en: ISSN 2193-1801
Editor: Springer Science and Business Media Deutschland GmbH
DOI: 10.1007/978-3-031-45275-8_33

A Protocol for Continual Explanation of SHAP (se abrirá en una nueva ventana)

Autores: Andrea Cossu, Francesco Spinnato, Riccardo Guidotti, Davide Bacciu
Publicado en: ESANN 2023 proceesdings, 2023
Editor: Ciaco - i6doc.com
DOI: 10.14428/ESANN/2023.ES2023-41

PyClust: Building Meta-learning Repositories for Clustering

Autores: Y. Poulakis, D. Petratos, C. Doulkeridis
Publicado en: 2025
Editor: 25th IEEE International Conference on Data Mining (ICDM'25)

FAIRness in Dataspaces: The Role of Semantics for Data Management

Autores: Marco Hauff, Lina Molinas Comet, Paul Moosmann, Christoph Lange, Ioannis Chrysakis, Johannes Theissen-Lipp
Publicado en: ISSN 1613-0073
Editor: CEUR Workshop Proceedings (CEUR-WS.org)

A Shape-Based Map Matching Approach for Geographic Transferability of Discriminative Subtrajectories

Autores: Cristiano Landi, Riccardo Guidotti
Publicado en: ISSN 1613-0073
Editor: CEUR Workshop Proceedings (CEUR-WS.org)

Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods (se abrirá en una nueva ventana)

Autores: Iason Kyriakopoulos, Yannis Theodoridis
Publicado en: 2025, ISSN 1112-3455
Editor: arXiv
DOI: 10.48550/ARXIV.2512.17257

Path-based traffic flow prediction

Autores: Efstratios Karkanis, Nikos Pelekis, Eva Chondrodima, Yannis Theodoridis
Publicado en: ISSN 1613-0073
Editor: CEUR Workshop Proceedings (CEUR-WS.org)

High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learning (se abrirá en una nueva ventana)

Autores: Mitja Žalik, Domen Mongus, Niko Lukač
Publicado en: Renewable Energy, ISSN 1879-0682
Editor: Elsevier
DOI: 10.1016/J.RENENE.2023.119868

A Survey on AutoML Methods and Systems for Clustering (se abrirá en una nueva ventana)

Autores: Yannis Poulakis, Christos Doulkeridis, Dimosthenis Kyriazis
Publicado en: ACM Transactions on Knowledge Discovery from Data, ISSN 1556-4681
Editor: Association for Computing Machinery
DOI: 10.1145/3643564

From Fossil Fuel to Electricity: Studying the Impact of EVs on the Daily Mobility Life of Users (se abrirá en una nueva ventana)

Autores: Mirco Nanni, Omid Isfahani Alamdari, Agnese Bonavita, Paolo Cintia
Publicado en: IEEE Transactions on Intelligent Transportation Systems, ISSN 1558-0016
Editor: IEEE
DOI: 10.1109/TITS.2023.3

Multi-Partner Project: Green.Dat.AI: A Data Spaces Architecture for Enhancing Green AI Services (se abrirá en una nueva ventana)

Autores: Ioannis Chrysakis, Evangelos Agorogiannis, Nikoleta Tsampanaki, Michalis Vourtzoumis, Eva Chondrodima, Yannis Theodoridis, Domen Mongus, Ben Capper, Martin Wagner, Aris Sotiropoulos, Fábio André Coelho, Cláudia Vanessa Brito, Panos Protopapas, Despina Brasinika, Ioanna Fergadiotou, Christos Doulkeridis
Publicado en: 2025 Design, Automation & Test in Europe Conference (DATE), 2025, ISSN 1530-1591
Editor: IEEE
DOI: 10.23919/DATE64628.2025.10992729

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