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

Projektinformationen

ExtremeXP

ID Finanzhilfevereinbarung: 101093164

DOI

10.3030/101093164

EK-Unterschriftsdatum 16 November 2022

Startdatum 1 Januar 2023

Enddatum 28 Februar 2026

Finanziert unter

• Digital, Industry and Space

Gesamtkosten

€ 10 011 820,00

EU-Beitrag

€ 10 011 820,00

Koordiniert durch

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

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

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.

Veröffentlichungen

Conference proceedings (24)

Optimizing Data Analytics Workflows through User-driven Experimentation

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

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

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

Capturing Analytical Intents from Text

Autoren: Gerard Pons, Miona Dimic, Besim Bilalli
Veröffentlicht in: 2020
Herausgeber: Springer
DOI: 10.1007/s10844-020-00604-x

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

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

Online ML Self-adaptation in Face of Traps

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

Non-Expert Level Analysis of Self-Adaptive System

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

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

Autoren: K. Larnier, J. Coves, G. Stephan and L. Dumas
Veröffentlicht in: Fifth Space for Hydrology Workshop, 2024
Herausgeber: ESA

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

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

Amalur: Data Integration Meets Machine Learning

Autoren: 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)
Veröffentlicht in: Crossref, 2023
DOI: 10.48550/arxiv.2205.09681

Discovery of Semantic Non-Syntactic Joins

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

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

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

Towards a Reference Component Model of Edge-Cloud Continuum

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

Mitigating Data Sparsity in Integrated Data through Text Conceptualization

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

Auditing for Spatial Fairness

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

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

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

Adaptive Strategies Metric Suite

Autoren: Koen Kraaijveld and Claudia Raibulet
Veröffentlicht in: 2024
Herausgeber: Springer, Cham
DOI: 10.1007/978-3-031-64182-4_14

An Approach for Intelligent Behaviour-Based Threat Modelling with Explanations

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

AutoFeat: Transitive Feature Discovery over Join Paths

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

Model Selection with Model Zoo via Graph Learning

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

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

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

HYPPO: Using Equivalences to Optimise Pipelines in Exploratory Machine Learning

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

Expert-Driven Monitoring of Operational ML Models

Autoren: Leest, Joran; Raibulet, Claudia; Gerostathopoulos, Ilias; Lago, Patricia
Veröffentlicht 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

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

Controlling Automatic Experiment-Driven Systems Using Statistics and Machine Learning

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

Peer reviewed articles (2)

Data Lakes: A Survey of Functions and Systems

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

Information Systems

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