QFLS: A Cloud-Based Framework for Supporting Big Healthcare Data Management and Analytics from Big Data Lakes: Definitions, Requirements, Models and Techniques

Alfredo Cuzzocrea; Alfredo Cuzzocrea; Selim Soufargi

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Paper

QFLS: A Cloud-Based Framework for Supporting Big Healthcare Data Management and Analytics from Big Data Lakes: Definitions, Requirements, Models and Techniques

Topics: Big Data Applications; Big Data Infrastructure; Data Analytics; Data Science; Data Structures and Data Management Algorithms

In Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA - Volume 1, 422-428, 2023 , Rome, Italy

Authors: Alfredo Cuzzocrea ^{1

;

2} and Selim Soufargi ¹

Affiliations: ¹ iDEA Lab, University of Calabria, Rende, Italy ; ² Department of Computer Science, University of Paris City, Paris, France

Keyword(s): Big Healthcare Data, Big Data Management, Big Data Analytics, Cloud-Based Frameworks.

Abstract: This paper introduces definitions, requirements, models and techniques of QUALITOP Federated Big Data Analytics Learning System (QFLS), a Cloud-based framework for supporting big healthcare data management and analytics from big data lakes. QFLS anatomy and main functionalities are described, along with the main software solutions proposed with the framework.

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Paper citation in several formats:

Cuzzocrea, A. and Soufargi, S. (2023). QFLS: A Cloud-Based Framework for Supporting Big Healthcare Data Management and Analytics from Big Data Lakes: Definitions, Requirements, Models and Techniques. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-664-4; ISSN 2184-285X, SciTePress, pages 422-428. DOI: 10.5220/0012092700003541

@conference{data23,
author={Alfredo Cuzzocrea. and Selim Soufargi.},
title={QFLS: A Cloud-Based Framework for Supporting Big Healthcare Data Management and Analytics from Big Data Lakes: Definitions, Requirements, Models and Techniques},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA},
year={2023},
pages={422-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012092700003541},
isbn={978-989-758-664-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - DATA
TI - QFLS: A Cloud-Based Framework for Supporting Big Healthcare Data Management and Analytics from Big Data Lakes: Definitions, Requirements, Models and Techniques
SN - 978-989-758-664-4
IS - 2184-285X
AU - Cuzzocrea, A.
AU - Soufargi, S.
PY - 2023
SP - 422
EP - 428
DO - 10.5220/0012092700003541
PB - SciTePress