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Authors: Yunji Zhang 1 ; Franck Ravat 2 ; Sébastien Laborie 1 and Philippe Roose 1

Affiliations: 1 Universite de Pau et des Pays de l’Adour, E2S UPPA, LIUPPA, Anglet, France ; 2 Institut de Recherche en Informatique de Toulouse - Université Toulouse Capitole, 31000, Toulouse, France

Keyword(s): Data Analysis, On-Read Schema, Spatio-Temporal Data, Multi-Perspective Analysis, Well-Being.

Abstract: The concept of ”Well-being” within local territories is increasingly recognized as a critical issue by local decision-makers. In the face of demographic shifting and population ageing, decision-makers need to anticipate demographic changes, plan land use, and shift land use promptly. They need a broader perspective that integrates various dimensions of the living environment for their territories. Therefore, it requires a system that can integrate different datasets and perspectives on various dimensions of ”Well-being”, including demographics, population distribution, land utilisation, transport, infrastructure development, social and business services, etc. It can perform comprehensive multi-perspective analyses based on integrated perspectives. However, the existing work on this topic mainly focuses on a single-perspective analysis, such as focusing exclusively on education. In order to fill this gap, this article aims to propose: (i) a mind map outlining the dimensions related to ”Well-being” and the associated data required for analyses; (ii) an on-read schema modelling framework for the storage, the cross-integration and the promoting accessibility of the multi-perspective data; and (iii) a modelling concept for multi-perspective analysis data to represent the various dimensions relating to ”Well-being”. (More)

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Paper citation in several formats:
Zhang, Y., Ravat, F., Laborie, S. and Roose, P. (2025). Multi-Perspective Analyses of Spatio-Temporal Data About Well-Being. In Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE; ISBN 978-989-758-742-9; ISSN 2184-4895, SciTePress, pages 80-91. DOI: 10.5220/0013282800003928

@conference{enase25,
author={Yunji Zhang and Franck Ravat and Sébastien Laborie and Philippe Roose},
title={Multi-Perspective Analyses of Spatio-Temporal Data About Well-Being},
booktitle={Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE},
year={2025},
pages={80-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013282800003928},
isbn={978-989-758-742-9},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Multi-Perspective Analyses of Spatio-Temporal Data About Well-Being
SN - 978-989-758-742-9
IS - 2184-4895
AU - Zhang, Y.
AU - Ravat, F.
AU - Laborie, S.
AU - Roose, P.
PY - 2025
SP - 80
EP - 91
DO - 10.5220/0013282800003928
PB - SciTePress