EXPeriment driven and user eXPerience oriented analytics for eXtremely Precise outcomes and decisions

Informazioni relative al progetto

ExtremeXP

ID dell’accordo di sovvenzione: 101093164

DOI

10.3030/101093164

Progetto chiuso

Data della firma CE 16 Novembre 2022

Data di avvio 1 Gennaio 2023

Data di completamento 28 Febbraio 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 10 011 820,00

Contributo UE

€ 10 011 820,00

Coordinato da

ATHINA-EREVNITIKO KENTRO KAINOTOMIAS STIS TECHNOLOGIES TIS PLIROFORIAS, TON EPIKOINONION KAI TIS GNOSIS
Greece

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

Demonstrators, pilots, prototypes (2)

Core framework services - Data and knowledge management

This deliverable will document the core framework services responsible for (a) the secure and distributed management of datasets, knowledge assets and experimentation-based learning outcomes and (b) defining and enforcing appropriate data authorisation by considering contextual information of the requestor, the artefact to be accessed and processed and their environment. It will include prototype libraries and/or tools and will document their implementation and usage information.

Data selection, integration, and simulation services

This deliverable will provide the first versions of (a) automated dataset selection strategies and feature augmentation methods, that will recommend the datasets that are fit-for-purpose for the current analytics task; (b) Analysis aware data integration and quality assurance services, that will support the interactive application of cleaning, interlinking, and enrichment methods to data gathered from various dispersed sources; (c) Data augmentation and simulation techniques, that will allow to detect the types and ranges of data that are missing in the datasets, in order to generate new data entries to balance the datasets with various augmentation techniques, and or deploy simulation models to produce new data. It will include prototype libraries and/or tools and will document their implementation and usage information.

Documents, reports (2)

Initial architecture, languages and models for complex experiment-driven analytics

This deliverable will report on the design the architecture of the ExtremeXP framework, as well as the modelling language and the underlying models that will support experiment-driven analytics. It will provide the specifications of a domain specific modelling language, as well as knowledge graphs for semantically representing experiments. Finally, it will describe the architecture of the framework, which will comprise several independent, self-contained, and elastic core services that can be used to store knowledge assets from experiments, collect evaluation data including user feedback, plan experiments, and enact them (either locally or on remote systems) using virtualized resources and serverless functions.

Use case requirements

This deliverable will report on the requirements elicited from each use-case and will issue technical designs of the use-case pilots while contributing functional and technical expectations over the ExtremeXP project. For each use-case, this process includes the selection of adequate datasets, the domain modelling, the variability point identification, the specification of the experiment models, the elicitation of user intents, and the determination of the technical settings for evaluation.

Pubblicazioni

Conference proceedings (41)

Distributed Data Security in Digital Health: Self-Sovereign Identity, Access Control, and Blockchain-based Log Records

Autori: Nicollas R. de Oliveira, Yago de R. dos Santos, Guilherme N. N. Barbosa, Lucio Henrik A. Reis, Ana Carolina R. Mendes, Marcela Tuler de Oliveira, Dianne S. V. de Medeiros, Diogo M. F. Mattos
Pubblicato in: 2024 6th International Conference on Blockchain Computing and Applications (BCCA), 2025
Editore: IEEE
DOI: 10.1109/BCCA62388.2024.10844453

Software Architecture for Data Intensive Systems Workshop

Autori: Ilias Gerostathopoulos et al.
Pubblicato in: First International Workshop on Software Architecture for Data-Intensive Systems (SADIS@ECSA 2025), 2025
Editore: First International Workshop on Software Architecture for Data-Intensive Systems (SADIS@ECSA 2025)

Optimizing Data Analytics Workflows through User-driven Experimentation

Autori: Keerthiga Rajenthiram
Pubblicato in: 3rd International Conference on AI Engineering – Software Engineering for AI (CAIN 2024), 2024
DOI: 10.1145/3644815.3644971

ExpEngine: A Tool for Data Analytics Workflow Optimization Through User-Driven Experimentation

Autori: Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos, Petr Hnětynka, Tomáš Bureš
Pubblicato in: 2024 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), 2024
Editore: IEEE
DOI: 10.1109/ACSOS-C63493.2024.00058

Urban Flash Flood Prediction Through High Resolution Deep Learning Approach

Autori: P. Delporte, et al.
Pubblicato in: LPS 2025, Conference Proceedings., 2025
Editore: ESA Int.

ExperimentLens: Interactive Visual Analytics and Explainability for ML Experiment Management.

Autori: Maroulis, S., Stamatopoulos, V., Gidarakos, P., Tsopelas, K., Masouras, N., Kozanis, K., Theologitis, N., Papastefanatos, G., Giannopoulos, G., & Nilsson, E
Pubblicato in: VLDB 2025 Workshops – GuideAI Workshop., 2025
Editore: VLDB 2025 Workshops – GuideAI Workshop.

Urban Flash Flood Prediction through High-Resolution Hydrodynamic Modelling and Machine Learning Approaches

Autori: Kévin Larnier, et al.
Pubblicato in: 2024 International Conference on Smart Applications, Communications and Networking (SmartNets), ISBN 9798350361482
DOI: 10.1109/SMARTNETS59842.2024.10641091

METIS: AN OPEN-ARCHITECTURE FOR BUILDING AI-READY CLOUD PLATFORMS – APPLICATION TO FOSTER RESEARCH ON HYDROLOGICAL MODELING

Autori: Vincent GAUDISSART, Yasmine BOULFANI, Kevin LARNIER, Gwendoline STEPHAN, Jacques COVES and Christophe TRIQUET
Pubblicato in: Proceedings of the 2023 conference on Big Data from Space (BiDS’23), Numero KJ-05-23-390-EN-N, 2023, ISBN 978-92-68-08696-4
Editore: Joint Research Centre (European Commission)
DOI: 10.2760/46796

Capturing Analytical Intents from Text

Autori: Gerard Pons, Miona Dimic, Besim Bilalli
Pubblicato in: 2020
Editore: Springer
DOI: 10.1007/s10844-020-00604-x

There is no Data Science without Data Governance: a Proposal Based on Knowledge Graphs

Autori: Besim Bilalli, Petar Jovanovic, Sergi Nadal, Anna Queralt, Oscar Romero
Pubblicato in: DOLAP 2024: 26th International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data, 2024, ISSN 1613-0073
Editore: CEUR

Partial Adaptive Indexing for Approximate Visual Analytics

Autori: Stavros Maroullis et al.
Pubblicato in: BigVis 2024, 2024
Editore: BigVis 2024

Online ML Self-adaptation in Face of Traps

Autori: Topfer, Michal; Plasil, Frantisek; Bures, Tomas; Hnetynka, Petr; Krulis, Martin; Weyns, Danny
Pubblicato in: Proceedings of ACSOS 2023, Toronto, Canada, 2023
DOI: 10.48550/arxiv.2309.05805

QueryER: A Framework for Fast Analysis-Aware Deduplication over Dirty Data

Autori: Giorgos Alexiou et al.
Editore: OpenProceedings.org
DOI: 10.48786/EDBT.2025.10

Non-Expert Level Analysis of Self-Adaptive System

Autori: Claudia Raibulet and Xiaojun Ling
Pubblicato in: ASOCA2023@ICSOC 2023, 2023
Editore: Springer, Singapore
DOI: 10.1007/978-981-97-0989-2_8

GLOVES: Global Counterfactual based Visual Explanations

Autori: Panagiotis Gidarakos et al.
Pubblicato in: 2024
Editore: OpenProceedings.org
DOI: 10.48786/EDBT.2025.92

Flash flood modeling and in urban areas using High Resolution hydrodynamic model and machine learning models

Autori: K. Larnier, J. Coves, G. Stephan and L. Dumas
Pubblicato in: Fifth Space for Hydrology Workshop, 2024
Editore: ESA

An Empirical Performance Comparison between Matrix Multiplication Join and Hash Join on GPUs

Autori: Wenbo Sun; Asterios Katsifodimos; Rihan Hai
Pubblicato in: 2023 IEEE 39th International Conference on Data Engineering Workshops (ICDEW), 2023, ISBN 979-8-3503-2245-3
Editore: IEEE
DOI: 10.1109/ICDEW58674.2023.00034

A Model-Based Approach to Experiment-Driven Evolution of ML Workflows

Autori: Petr Hnětynka, Tomáš Bureš, Ilias Gerostathopoulos, Milad Abdullah, Keerthiga Rajenthiram
Pubblicato in: Proceedings of the 13th International Conference on Model-Based Software and Systems Engineering, 2025
Editore: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0013380500003896

Amalur: Data Integration Meets Machine Learning

Autori: Hai, R. (author); Koutras, C. (author); Ionescu, A. (author); Li, Z. (author); Sun, W. (author); van Schijndel, Jessie (author); Kang, Yan (author); Katsifodimos, A (author)
Pubblicato in: Crossref, 2023
DOI: 10.48550/arxiv.2205.09681

Discovery of Semantic Non-Syntactic Joins

Autori: Marc Maynou, Sergi Nadal
Pubblicato in: DOLAP 2024: 26th International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data, 2024, ISSN 1613-0073
Editore: CEUR

Evolvability of Machine Learning-based Systems : An Architectural Design Decision Framework

Autori: Joran Leest, Ilias Gerostathopoulos, Claudia Raibulet
Pubblicato in: 2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C), 2023
Editore: IEEE
DOI: 10.1109/ICSA-C57050.2023.00033

Towards a Reference Component Model of Edge-Cloud Continuum

Autori: Danylo Khalyeyev, Tomáš Bureš, and Petr Hnětynka
Pubblicato in: 20th IEEE International Conference on Software Architecture (ICSA 2023), 2023
Editore: IEEE
DOI: 10.1109/ICSA-C57050.2023.00030

Towards Continuous Experiment-Driven MLOps

Autori: Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos, Petr Hnětynka, Tomáš Bureš, Gerard Pons, Besim Bilalli, Anna Queralt
Pubblicato in: 2025 IEEE/ACM 4th International Conference on AI Engineering – Software Engineering for AI (CAIN), 2025
Editore: IEEE
DOI: 10.1109/CAIN66642.2025.00018

Robin: A Systematic Literature Mapping Management Tool

Autori: Milad Abdullah, Michal Töpfer, Tomáš Bureš
Pubblicato in: 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2024
Editore: IEEE
DOI: 10.1109/SEAA64295.2024.00051

Mitigating Data Sparsity in Integrated Data through Text Conceptualization

Autori: Md Ataur Rahman, Sergi Nadal, Oscar Romero, Dimitris Sacharidis
Pubblicato in: 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2024
Editore: IEEE
DOI: 10.1109/ICDE60146.2024.00269

Auditing for Spatial Fairness

Autori: Sacharidis, Dimitris; Giannopoulos, Giorgos; Papastefanatos, George; Stefanidis, Kostas
Pubblicato in: 2023
DOI: 10.48550/arxiv.2302.12333

MAPE-K based Guidelines for Designing Reactive and Proactive Self-Adaptive Systems

Autori: Hendrik Jilderda and Claudia Raibulet
Pubblicato in: Post Proceedings of the ECSA 2023 Workshops, in press, 2023
Editore: Springer, Cham
DOI: 10.1007/978-3-031-66326-0_4

Adaptive Strategies Metric Suite

Autori: Koen Kraaijveld and Claudia Raibulet
Pubblicato in: 2024
Editore: Springer, Cham
DOI: 10.1007/978-3-031-64182-4_14

An Approach for Intelligent Behaviour-Based Threat Modelling with Explanations

Autori: S. Preetam, M. Compastié, V. Daza, and S. Siddiqui,
Pubblicato in: 2023, ISSN 2832-2231
Editore: IEEE
DOI: 10.1109/NFV-SDN59219.2023.10329587

Surrogate Modelling and User‑In‑The‑Loop Experimentation for Urban Flood Prediction: The ExtremeXP Approach

Autori: P. Delporte, et al.
Pubblicato in: ESA Living Planet Symposium 2025, Milan, Italy, 2025
Editore: ESA Int

Interpreting Workflow Architectures by LLMs

Autori: Michal Töpfer, Tomáš Bureš, František Plášil, Petr Hnětynka
Pubblicato in: Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering, 2025
Editore: SCITEPRESS - Science and Technology Publications
DOI: 10.5220/0013358000003928

Extending UEBA for Emerging Threats

Autori: Carolina Ferández et al.
Pubblicato in: 2024
Editore: GEANT Security Days
DOI: 10.2760/46796

Experiment Cards: A Documentation Framework for Trustworthy AI Experiments

Autori: Georgia Gkioka, Dimitris Apostolou, Yiannis Verginadis, Gregoris Mentzas
Pubblicato in: 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI), 2025
Editore: IEEE
DOI: 10.1109/ICTAI66417.2025.00065

A Combined Approach to Performance Regression Testing Resource Usage Reduction

Autori: Milad Abdullah, David Georg Reichelt, Vojtěch Horký, Lubomír Bulej, Tomáš Bureš, Petr Tůma
Pubblicato in: Proceedings of the 21st International Conference on Predictive Models and Data Analytics in Software Engineering, 2025
Editore: ACM
DOI: 10.1145/3727582.3728690

AutoFeat: Transitive Feature Discovery over Join Paths

Autori: Andra Ionescu, Kiril Vasilev, Florena Buse, Rihan Hai, Asterios Katsifodimos
Pubblicato in: 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2024
Editore: IEEE
DOI: 10.1109/ICDE60146.2024.00150

Model Selection with Model Zoo via Graph Learning

Autori: Ziyu Li, Hilco van der Wilk, Danning Zhan, Megha Khosla, Alessandro Bozzon, Rihan Hai
Pubblicato in: 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2024
Editore: IEEE
DOI: 10.1109/ICDE60146.2024.00088

Early Stopping of Non-productive Performance Testing Experiments Using Measurement Mutations

Autori: Milad Abdullah, Lubomír Bulej, Tomáš Bureš, Vojtěch Horký, Petr Tůma
Pubblicato in: 2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2023, ISBN 979-8-3503-4235-2
Editore: IEEE
DOI: 10.1109/SEAA60479.2023.00022

HYPPO: Using Equivalences to Optimise Pipelines in Exploratory Machine Learning

Autori: Antonis Kontaxakis, Dimitris Sacharidis, Alkis Simitsis, Alberto Abelló, Sergi Nadal:
Pubblicato in: 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2024
Editore: IEEE
DOI: 10.1109/ICDE60146.2024.00024

Expert-Driven Monitoring of Operational ML Models

Autori: Leest, Joran; Raibulet, Claudia; Gerostathopoulos, Ilias; Lago, Patricia
Pubblicato in: International Conference on Software Engineering (ICSE), 2024, ISBN 979-8-4007-0217-4
DOI: 10.48550/arxiv.2401.11993

Visualization-aware Time Series Min-Max Caching with Error Bound Guarantees

Autori: Stavros Maroulis, Vassilis Stamatopoulos, George Papastefanatos, Manolis Terrovitis
Pubblicato in: 50th International Conference on Very Large Databases (VLDB 2024), 2024
Editore: VLDB Endowment
DOI: 10.14778/3659437.3659460

Controlling Automatic Experiment-Driven Systems Using Statistics and Machine Learning

Autori: Milad Abdullah
Pubblicato in: Postproceedings of ECSA 2022 Tracks and Workshops, 2023
DOI: 10.1007/978-3-031-36889-9_9

Peer reviewed articles (6)

An architectural perspective on MLOps: Structures, processes, tools, and stakeholders

Autori: Faezeh Amou Najafabadi, Justus Bogner, Ilias Gerostathopoulos, Patricia Lago
Pubblicato in: Information and Software Technology, Numero 193, 2026, ISSN 0950-5849
Editore: Elsevier BV
DOI: 10.1016/J.INFSOF.2026.108029

Data Lakes: A Survey of Functions and Systems

Autori: Rihan Hai; Christos Koutras; Christoph Quix; Matthias Jarke
Pubblicato in: IEEE Transactions on Knowledge and Data Engineering, 2023, ISSN 1041-4347
Editore: IEEE
DOI: 10.48550/arxiv.2106.09592

Information Systems

Autori: Joseph Giovanelli, Besim Bilalli, Alberto Abelló, Fernando Silva-Coira, Guillermo de Bernardo
Pubblicato in: Information Systems, Numero 120, 2024, ISSN 0306-4379
Editore: Elsevier Science & Technology
DOI: 10.1016/j.is.2023.102314

RBD24 : A labelled dataset with risk activities using log application data

Autori: Albert Calvo, Santiago Escuder, Nil Ortiz, Josep Escrig, Maxime Compastié
Pubblicato in: Computers & Security, Numero 150, 2025, ISSN 0167-4048
Editore: Elsevier BV
DOI: 10.1016/J.COSE.2024.104290

NFT-based Data Provenance for AI Transparency in Enterprise Information Systems

Autori: Yiannis Verginadis, Orestis Almpanoudis, Dimitris Apostolou, Marcela T. de Oliveira, Gregoris Mentzas
Pubblicato in: Procedia Computer Science, Numero 256, 2025, ISSN 1877-0509
Editore: Elsevier BV
DOI: 10.1016/J.PROCS.2025.02.153

Reproducible experiments for generating pre-processing pipelines for AutoETL

Autori: Joseph Giovanelli, Besim Bilalli, Alberto Abelló, Fernando Silva-Coira, Guillermo de Bernardo
Pubblicato in: Information Systems, Numero 120, 2025, ISSN 0306-4379
Editore: Elsevier BV
DOI: 10.1016/J.IS.2023.102314

Book chapters (9)

GLOVES 2.0: Global Counterfactual-Based Visual Explanations

Autori: Nikolas Theologitis, Panagiotis Gidarakos, Stavros Maroulis, Loukas Kavouras, Giorgos Giannopoulos, George Papastefanatos
Pubblicato in: Lecture Notes in Computer Science, Software Architecture. ECSA 2025 Tracks and Workshops, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-04403-7_28

Reference Architecture of MLOps Workflows

Autori: Faezeh Amou Najafabadi
Pubblicato in: Lecture Notes in Computer Science, Software Architecture. ECSA 2024 Tracks and Workshops, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-71246-3_6

Accelerating Entity Resolution Through Vectorized Meta-blocking on GPUs

Autori: Nikolas Stamatopoulos, Vassilis Stamatopoulos, Giorgos Alexiou, Giorgos Giannopoulos, George Papastefanatos
Pubblicato in: Communications in Computer and Information Science, New Trends in Database and Information Systems, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-05727-3_14

Temporal Harmonization of Heterogeneous Software Logs: A Unified Model for Time-Series Analysis

Autori: Milad Abdullah, Petr Hnětynka, Jiyan Salim Mahmud
Pubblicato in: Lecture Notes in Computer Science, Software Architecture. ECSA 2025 Tracks and Workshops, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-04403-7_29

AutoML: A Tertiary Study of Phases, Methods, Tools, and Frameworks

Autori: Keerthiga Rajenthiram, Pauline Delporte, Patricia Lago
Pubblicato in: Lecture Notes in Computer Science, Software Architecture. ECSA 2025 Tracks and Workshops, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-04403-7_26

Explainable AI for cybersecurity decisions: challenges and opportunities

Autori: Albert Calvo, Sonu Preetam, Maxime Compastié
Pubblicato in: Explainable AI for Communications and Networking, 2025
Editore: Elsevier
DOI: 10.1016/B978-0-44-329135-7.00018-7

An Analysis of MLOps Architectures: A Systematic Mapping Study

Autori: Faezeh Amou Najafabadi, Justus Bogner, Ilias Gerostathopoulos, Patricia Lago
Pubblicato in: Lecture Notes in Computer Science, Software Architecture, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70797-1_5

TimeVizBench: An Interactive Platform for Evaluating Techniques for Efficient Large Time Series Visualization

Autori: Vassilis Stamatopoulos, Stavros Maroulis, Christos Pantoleon, George Papastefanatos, Panos Vassiliadis
Pubblicato in: Communications in Computer and Information Science, New Trends in Database and Information Systems, 2025
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-032-05727-3_8

Knowledge Graphs for Enhancing Large Language Models in Entity Disambiguation

Autori: Gerard Pons, Besim Bilalli, Anna Queralt
Pubblicato in: Lecture Notes in Computer Science, The Semantic Web – ISWC 2024, 2024
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-77844-5_9

Thesis and dissertations (1)

Evaluating Robustness of Machine Learning Models against Adversarial Attacks: Techniques, Countermeasures, and Performance Analysis

Autori: Nil Ortiz, Albert Calvo
Pubblicato in: JNIC
Editore: Lenguajes y Sistemas Informáticos