Extending Federated Data Platforms in the Cloud Continuum for Manufacturing and Intralogistics

Krista Mätäsniemi, Teemu Toroi, David Hästbacka

2025

Abstract

Federated data platforms (FDPs), or data spaces, are frameworks that facilitate data sharing between diverse data sources and stakeholders. FDPs are critical enablers in the 2020 European Data Strategy where industrial data is a strategic investment area. Industrial use cases can involve high data volumes and velocity despite operating in resource-constrained environments. FDPs have been proven in inter-company data exchanges and are typically implemented on scalable cloud platforms. This study explores the possibility of extending FDPs in the cloud continuum (CC) by examining how the technical requirements of FDP building blocks align with the drivers, characteristics, and enablers of CC layers. The study introduces an analysis framework for finding the optimal placement of building blocks along CC. It also shows that transferring FDP components connected to high data volumes closer to the edge can make FDPs more effective and better suited for manufacturing and intralogistics use cases. The study concludes that there is an architectural fit between FDP functionalities and the characteristics of the CC, and suggests that FDP usability and performance should be studied empirically.

Paper Citation

in Harvard Style

Mätäsniemi K., Toroi T. and Hästbacka D. (2025). Extending Federated Data Platforms in the Cloud Continuum for Manufacturing and Intralogistics. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS; ISBN 978-989-758-769-6, SciTePress, pages 417-427. DOI: 10.5220/0013732100004000

in Bibtex Style

@conference{kmis25,
author={Krista Mätäsniemi and Teemu Toroi and David Hästbacka},
title={Extending Federated Data Platforms in the Cloud Continuum for Manufacturing and Intralogistics},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS},
year={2025},
pages={417-427},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013732100004000},
isbn={978-989-758-769-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KMIS
TI - Extending Federated Data Platforms in the Cloud Continuum for Manufacturing and Intralogistics
SN - 978-989-758-769-6
AU - Mätäsniemi K.
AU - Toroi T.
AU - Hästbacka D.
PY - 2025
SP - 417
EP - 427
DO - 10.5220/0013732100004000
PB - SciTePress