Data Discovery Platform with Generalized Exploratory, Management, and Search Capabilities

Informazioni relative al progetto

DataGEMS

ID dell’accordo di sovvenzione: 101188416

DOI

10.3030/101188416

Data della firma CE 25 Ottobre 2024

Data di avvio 1 Gennaio 2025

Data di completamento 31 Dicembre 2027

Finanziato da

Research infrastructures

Costo totale

€ 6 688 960,00

Contributo UE

€ 6 688 960,00

6 688 960,00

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

D4.3a User Assistance Services

This deliverable presents the first version of the User Assistance Services

D3.3a Data Discovery Services

This software deliverable will present the first version of the Dataset Discovery Services. It will provide implementation progress, blocking issues, and future plans for components dealing with (a) in-dataset discovery, (b) cross-dataset discovery, (c) extracting and utilising data patterns, and (d) packaging of dataset into meaningful bundles for the user.

D5.3a Dataset and Model Management Services

This deliverable presents the first prototype version of Dataset and Model Management Services. It will be based on state-of-the-art systems and will include basic functionalities for the MoMa and Polyglot Query engine for the execution of dataset discovery. It will provide support for at least 2 basic structured and semi-structured data-types, e.g., relational data and CSV files.

D6.3a Operational Services & Integration Components

This deliverable presents the first version Operational Services and Integration Components of the project platform

D2.3a Dataset Profiling Services

This deliverable presents the first version of the a) methods for generating quantitative and qualitative data insights, (b) adapters to generate semantic representations of a dataset, (c) methods for generating summaries in natural language and as graphs.In addition will present the first version of (a) multimodal methods to extract information from unstructured data (b) integrated with the semantic precision and grounding provided by KGs and online algorithms for processing streaming data, which may be structured or unstructured

Data Storage, Management and Access Architecture Report

This deliverable presents the design of the architecture for the Data Storage, management and Access components. It will describe the components to store datasets and their metadata, the machine learning models, the virtual knowledge graph layer, as well as the user profile, the polyglot engine, and performance monitoring components.

D1.4a Short policy brief on the expected impact from the project

The policy brief aims at assessing the impact of the implementation of DataGEMS across different sectors and providing stakeholders with actionable insights in relation to its use and adoption. The goal of this deliverable is checking the different platform capabilities against their benefits and challenges in multiple contexts including real-life use cases, in order to draft policy recommendations for optimising, improving and adapting DataGEMS, addressing any potential issues that may be identified such as privacy or developments on Artificial Intelligence, fostering further collaboration through public-private partnerships and ensuring that it can continue benefiting future generations.

User Assistance Architecture Report

This deliverable will present the whole architecture of the User Assistance algorithms and methods involving Query Recommendation, Query Disambiguation, Dataset Recommendation and Explanations

Dataset Profiling Design Report

This deliverable aims to provide the design of the Dataset Profiling for Structured Datasets, Unstructured Datasets as well as streaming data which may be structured or unstructured

Pilots Specifications & Design Report

This deliverable presents the Specifications and Design of the 4 Pilots

Dataset Discovery Architecture Report

This deliverable presents a full description of the dataset discovery architecture with well defined components responsible for allowing the user to exploit as efficiently as possible data provided by DataGEMs. The deliverable will describe how the project plans offering both in-dataset and cross-dataset discovery along with utilities such as exploiting data analytics patterns and packaging of datasets into bundles.

D7.4a Pilot's Software Components

This deliverable presents the first version of the Pilots' Software Components

Pilot Requirements Report

This deliverable presents the whole set of Requirements for the 4 Pilots

Awareness Raising, Communication, Dissemination, Outreach & Engagement Plan

This deliverable presents the Dissemination and Communication plan in terms of means and timeframe of activities, in combination with stakeholder identification and targeting. The Dissemination and Communication plan will be updated as necessary to ensure its relevance and effectiveness.

D8.3a Report on Dissemination, Communication and Liaison Activities

This deliverable depicts the process and the results of the establishment of liaison activities with relevant initiatives/taskforces/projects that operate in the areas of Open Science, EOSC and EU Research Infrastructures.

D1.5a Ethics Compliance

The goal of this deliverable is assessing ethical aspects and data implications of DataGEMS, including any data protection elements that may be relevant for the platform. This will be achieved through an ethical impact assessment that includes an evaluation of compliance with fundamental rights and main ethical principles, with a specific separate analysis for the use of Artificial Intelligence as applicable, taking into account the Ethics Guidelines for Trustworthy AI published by the AI High Level Expert Group and any provisions that may need to be observed according to the AI Act. A data compliance analysis will also be carried out, ensuring that DataGEMS complies with the applicable legal framework in this field, covering the GDPR, the Regulation on a framework for the free-flow of non-personal data in the EU and any concerned national laws.

Platform Architecture Design Report

This deliverable will present the Architecture Design of the Project Platform and its key specifications. It will describe the various components required, including their communication pathways and dependencies. Emphasis will be placed on providing a clear, diagram-based design of these components while ensuring flexibility for future modifications and additions.

Platform Development Manual

This deliverable will present the Development Manual of the Project Platform

D7.5a Pilot Implementation Evaluation Report

This deliverable presents the first version of the evaluation of the pilots implementation

D8.2a Material for Awareness, Communication, Dissemination and Outreach

This deliverable deals with the delivery of visual and textual representation of the project to be used in the project’s dissemination activities, be it web, face-to-face or printed ones. It also establishes guidelines for promotion and use of materials delivered. Apart from templates, the task will deliver early in the project lifetime generic material for reuse in several face-to-face, printed and online occasions and in several languages.

D1.3a Data Management Plan

This deliverable lays a solid roadmap for management of data, software, workflows, and any other research output expected by the project. Due to the data-centric nature of the project, the deliverable will describe in detail the whole lifecycle of data in DataGEMs including acquisition, storing, updating, and archiving along with a clear plan of ensuring accessibility and reusability of all project outputs.

Pubblicazioni

Comparison and Analysis of Value Linking in Text-to-SQL systems: [Experiments & Analysis]

Autori: Apostolos Koukouvinis, George Katsogiannis-Meimarakis, Georgia Koutrika
Pubblicato in: Proceedings of the ACM on Management of Data, Numero 4, 2026, ISSN 2836-6573
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3802029

$k$-Graph: A Graph Embedding for Interpretable Time Series Clustering

Autori: Boniol, Paul; Tiano, Donato; Bonifati, Angela; Palpanas, Themis
Pubblicato in: IEEE Transactions on Knowledge and Data Engineering, 2025, ISSN 1558-2191
Editore: IEEE
DOI: 10.48550/ARXIV.2502.13049

Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Art

Autori: Ilias Azizi, Karima Echihabi, Themis Palpanas
Pubblicato in: Proceedings of the ACM on Management of Data, Numero 3, 2026, ISSN 2836-6573
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3709693

LeaFi: Data Series Indexes on Steroids with Learned Filters

Autori: Qitong Wang, Ioana Ileana, Themis Palpanas
Pubblicato in: Proceedings of the ACM on Management of Data, Numero 3, 2026, ISSN 2836-6573
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3709701

Graphint: Graph-Based Time Series Clustering Visualisation Tool

Autori: Boniol, Paul; Tiano, Donato; Bonifati, Angela; Palpanas, Themis
Pubblicato in: 2025 IEEE 41st International Conference on Data Engineering (ICDE), 2025, ISSN 2375-026X
Editore: IEEE
DOI: 10.48550/ARXIV.2503.07698

DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search

Autori: Manos Chatzakis, Yannis Papakonstantinou, Themis Palpanas
Pubblicato in: Proceedings of the ACM on Management of Data, Numero 3, 2026, ISSN 2836-6573
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3749160

APEROL: Adaptive Parallel Edge-to-Cloud Runtime Optimization for Layered Workflow Execution

Autori: Dimitrios Banelas, Alkis Simitsis, Nikos Giatrakos
Pubblicato in: Proceedings of the VLDB Endowment, Numero 19, 2026, ISSN 2150-8097
Editore: Association for Computing Machinery (ACM)
DOI: 10.14778/3773749.3773755

Model reusability in Reinforcement Learning

Autori: Nikookar, Sepideh; Namazi Nia, Sohrab; Basu Roy, Senjuti; Amer-Yahia, Sihem; Omidvar-Tehrani, Behrooz
Pubblicato in: The VLDB Journal, 2025, ISSN 0949-877X
Editore: Springer Nature
DOI: 10.1007/S00778-025-00920-0

Multi-objective Clustering Algorithm Applied to the MathE Categorization Problem

Autori: Beatriz Flamia Azevedo, Gabriel A. Leite, M. Fátima Pacheco, Florbela P. Fernandes, Ana Maria A. C. Rocha, Ana I. Pereira
Pubblicato in: Information Systems Frontiers, 2026, ISSN 1387-3326
Editore: Springer Science and Business Media LLC
DOI: 10.1007/S10796-025-10674-3

Subspace Collision: An Efficient and Accurate Framework for High-dimensional Approximate Nearest Neighbor Search

Autori: Jiuqi Wei; Xiaodong Lee; Zhenyu Liao 0001; Themis Palpanas; Botao Peng
Pubblicato in: Proceedings of the ACM on Management of Data, 2025, ISSN 1557-7341
Editore: PACMMOD
DOI: 10.48550/ARXIV.2411.14754

VUS: effective and efficient accuracy measures for time-series anomaly detection

Autori: Paul Boniol; Ashwin K. Krishna; Marine Bruel; Qinghua Liu; Mingyi Huang; Themis Palpanas; Ruey S. Tsay; Aaron J. Elmore; Michael J. Franklin; John Paparrizos
Pubblicato in: The VLDB Journal, 2025, ISSN 0949-877X
Editore: Springer Nature
DOI: 10.48550/ARXIV.2502.13318

R-Fairness: Assessing Fairness of Ranking in Subjective Data

Autori: Balzotti, Lorenzo; Firmani, Donatella; Mathew, Jerin George; Torlone, Riccardo; Amer-Yahia, Sihem
Pubblicato in: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025, ISSN 0736-587X
Editore: Association for Computational Linguistics
DOI: 10.5281/ZENODO.15504617

Reducing Human Effort in Evaluating Small and Medium Language Models as Students and as Teachers

Autori: Oleh Prostakov, Viacheslav Hodlevskyi, Nassim Bouarour, Adam Sanchez-Ayte, Noha Ibrahim, and Sihem Amer-Yahia
Pubblicato in: 2025, ISSN 2150-8097
Editore: PVLDB

Optimizing Source Selection for Tuple-Value Discovery

Autori: Ahmad Fares, Georgia Troullinou, Silviu Maniu, Sihem Amer-Yahia
Pubblicato in: 2025, ISSN 2150-8097
Editore: VLDB

DeviceScope: An Interactive App to Detect and Localize Appliance Patterns in Electricity Consumption Time Series

Autori: Adrien Petralia, Paul Boniol, Philippe Charpentier, Themis Palpanas
Pubblicato in: 2025 IEEE 41st International Conference on Data Engineering (ICDE), 2025
Editore: IEEE
DOI: 10.1109/ICDE65448.2025.00350

Few Labels are All you Need: A Weakly Supervised Framework for Appliance Localization in Smart-Meter Series

An End-to-End Re-Evaluation of Table Entity-Linkers

Autori: Christensen Martin Pekár, Lissandrini Matteo, Hose Katja
Pubblicato in: 2026
Editore: Zenodo

User-Friendly Foundation Model Adapters for Multivariate Time Series Classification

Autori: Romain Ilbert, Vasilii Feofanov, Malik Tiomoko, Ievgen Redko, Themis Palpanas
Pubblicato in: 2025 IEEE 41st International Conference on Data Engineering Workshops (ICDEW), 2025
Editore: IEEE
DOI: 10.1109/ICDEW67478.2025.00024

Optimizing UDF Queries in SQL Data Engines

Autori: Konstsntinos Chasialis, Yannis Foufoulas, Alkis Simitsis, Yannis Ioannidis
Pubblicato in: 2026, ISSN 2367-2005
Editore: OpenProceedings

PG-HIVE: Hybrid Incremental Schema Discovery for Property Graphs

Autori: Sofia Sideri, Georgia Troullinou, Elisjana Ymeralli, Vasilis Efthymiou, Dimitris Plexousakis, Haridimos Kondylakis
Pubblicato in: 2026, ISSN 2367-2005
Editore: OpenProceedings

NILMFormer: Non-Intrusive Load Monitoring that Accounts for Non-Stationarity

Autori: Adrien Petralia, Philippe Charpentier, Youssef Kadhi, Themis Palpanas
Pubblicato in: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2, 2026
Editore: ACM
DOI: 10.1145/3711896.3737251

Towards a Neural Database Execution Engine

Autori: Christos Tsapelas
Pubblicato in: 2025
Editore: CEUR-WS

Hyppo: Efficient Discovery and Execution of Data Science Pipelines in Collaborative Environments

Autori: Antonios Kontaxakis, Dimitris Sacharidis, Alkis Simitsis, Alberto Abelló, Sergi Nadal
Pubblicato in: 2025, ISSN 2367-2005
Editore: OpenProceedings

In-depth Analysis of LLM-based Schema Linking

Autori: George Katsogiannis-Meimarakis, Katsiaryna Mirylenka, Paolo Scotton, Francesco Fusco, Abdel Labbi
Pubblicato in: 2026, ISSN 2367-2005
Editore: OpenProceedings

Analysis of Text-to-SQL Benchmarks: Limitations, Challenges

Autori: Anna Mitsopoulou,Georgia Koutrika
Pubblicato in: 2025
Editore: OpenProceedings

Flood Detection in Switzerland Using Sentinel-2 Satellite Imagery

Autori: Claude Lehmann, Kurt Stockinger, Pavel Sulimov
Pubblicato in: 2026 IEEE Swiss Conference on Data Science and AI (SDS), 2026
Editore: IEEE
DOI: 10.1109/SDS70563.2026.00033

Multi-Modal Data Exploration via Language Agents

Autori: Farhad Nooralahzadeh, Yi Zhang, Jonathan Fürst, Kurt Stockinger
Pubblicato in: Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2026
Editore: The Asian Federation of Natural Language Processing and The Association for Computational Linguistics
DOI: 10.18653/V1/2025.FINDINGS-IJCNLP.47

UDFB <scp>ench</scp> : A Tool for Benchmarking UDF Queries on SQL Engines

Autori: Yannis Foufoulas, Theoni Palaiologou, Alkis Simitsis
Pubblicato in: Companion of the 2025 International Conference on Management of Data, 2025
Editore: ACM
DOI: 10.1145/3722212.3725139

What Drives Learned Optimizer Performance? A Systematic

Autori: Kostas Mparmparousis, Christos Tsapelas, Georgia Koutrika
Pubblicato in: OpenProceedings, 2026, ISSN 2367-2005
Editore: OpenProceedings

The UDFBench Benchmark for General-purpose UDF Queries

Autori: Yannis Foufoulas, Theoni Palaiologou, and Alkis Simitsis
Pubblicato in: 2025
Editore: PVLDB
DOI: 10.14778/3746405.3746409

Problem Solved? Information Extraction Design Space for Layout-Rich Documents using LLMs

Autori: Gaye Colakoglu, Gürkan Solmaz, Jonathan Fürst
Pubblicato in: Findings of the Association for Computational Linguistics: EMNLP 2025, 2025
Editore: Association for Computational Linguistics
DOI: 10.18653/V1/2025.FINDINGS-EMNLP.973

HAIDES: Adaptive Approximation of Inference Queries over Unstructured Data

Autori: Christos C. Papadopoulos, Alkis Simitsis, Torben Bach Pedersen
Pubblicato in: 2025 IEEE 41st International Conference on Data Engineering (ICDE), 2025
Editore: IEEE
DOI: 10.1109/ICDE65448.2025.00181

Linear Transformations for Privacy-Preserving Machine Learning

Autori: Pavel Sulimov, Sergey Eremeykin
Pubblicato in: 2026 IEEE Swiss Conference on Data Science and AI (SDS), 2026, ISSN 2835-3420
Editore: IEEE
DOI: 10.1109/SDS70563.2026.00034

Supervised Cardinality Estimation for Similarity Queries on Knowledge Graphs

Autori: Georgios Chatzigeorgakidis, Dimitrios Skoutas, Alkis Simitsis
Pubblicato in: 2026, ISSN 2472-9671
Editore: IEEE

Evaluating and Generating Query Workloads for High Dimensional Vector Similarity Search

Autori: Matteo Ceccarello, Alexandra Levchenko, Ioana Ileana, Themis Palpanas
Pubblicato in: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2, 2026
Editore: ACM
DOI: 10.1145/3711896.3737383

Jazero: A Semantic Table Search System

Autori: Christensen, Martin Pekár; Lissandrini, Matteo; Hose, Katja
Pubblicato in: 2026
DOI: 10.5281/ZENODO.18935699

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