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Data Science approach for a cross-disciplinary understanding of urban phenomena: Application to energy efficiency of buildings
Abstract : Our goal is to develop theoretical and practical tools to model, explore and exploit heterogeneous data from various sources in order to understand a phenomenon. We focus on a generic model for data acquisition campaigns based on the concept of generic sensor. The concept of generic sensor is centered on acquired data and on their inherent multi-dimensional structure, to support complex domain-specific or field-oriented analysis processes. We consider that a methodological breakthrough, based on Data Science as a pivot for interdisciplinary dialog, may pave the way to deep understanding of voluminous and heterogeneous scientific data sets. Our use case concerns energy efficiency of buildings to understand relationship between physical phenomena and user behaviors. This project concern computer scientists from the LIRIS, social and urban scientists from the EVS laboratory and thermal scientists from the CETHIL laboratory. The aim of this paper is to give a synthetic presentation of our methodology and main results.
https://hal.archives-ouvertes.fr/hal-01192716
Contributor : Sylvie Servigne Connect in order to contact the contributor
Submitted on : Friday, December 4, 2020 - 1:51:09 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:09 PM
Long-term archiving on: : Friday, March 5, 2021 - 7:00:22 PM
Contributor : Sylvie Servigne Connect in order to contact the contributor
Submitted on : Friday, December 4, 2020 - 1:51:09 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:09 PM
Long-term archiving on: : Friday, March 5, 2021 - 7:00:22 PM
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