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Diagnostic qualité et apurement des données de mobilité quotidienne issues de l’enquête mixte et longitudinale Mobi’Kids

Abstract : This paper aims at proposing a data quality diagnosis and cleansing data methodology experimented on an individual mobility survey (Mobi’Kids program). The first section presents the theoretical approach to highlight the issue of a data quality diagnosis applied to heterogeneous data collected from mixed methods (GPS tracks, surveys, observations). Secondly, two typologies of major errors are discussed according to their origin (GPS, algorithm, survey) and their nature (completeness, accuracy, consistency). A processing chain is thirdly defined to improve both internal and external data quality in order to the perspective of a replicable methodology.
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Submitted on : Thursday, December 2, 2021 - 11:54:29 AM
Last modification on : Wednesday, April 27, 2022 - 4:04:31 AM
Long-term archiving on: : Thursday, March 3, 2022 - 7:12:40 PM

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Sylvestre Duroudier, Sonia Chardonnel, B. Mericskay, Isabelle Andre-Poyaud, Olivier Bedel, et al.. Diagnostic qualité et apurement des données de mobilité quotidienne issues de l’enquête mixte et longitudinale Mobi’Kids. Revue Internationale de Géomatique, Lavoisier, 2020, 30 (1-2), pp.127-148. ⟨10.3166/rig.2020.00105⟩. ⟨hal-03254291⟩

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