Explorative pedestrian mobility GPS data from a citizen science experiment in a neighbourhood
This data-set contains high resolution GPS records from a single day pedestrian mobility of 19 groups (72 participants) from three different communities of the "Primer de Maig" neighbourhood of Granollers (Spain). The experiment took place in May 2022. The participants explored the neighbo...
| Autores: | , |
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| Tipo de recurso: | conjunto de datos |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Consorci de Serveis Universitaris de Catalunya (CSUC) |
| Repositorio: | CORA.Repositori de Dades de Recerca |
| OAI Identifier: | oai:dnet:cora.rdr____::b1c28be5372da99429eed032759b29a2 |
| Acceso en línea: | https://doi.org/10.34810/DATA898 |
| Access Level: | acceso abierto |
| Palabra clave: | Computer and Information Science Physics Social Sciences Other Citizen science Computational social science Human mobility GPS City Urbanism |
| Sumario: | This data-set contains high resolution GPS records from a single day pedestrian mobility of 19 groups (72 participants) from three different communities of the "Primer de Maig" neighbourhood of Granollers (Spain). The experiment took place in May 2022. The participants explored the neighbourhood in groups and chose different places to stop and perform various festive actions, while recording the trajectory using the Wikiloc app. These stopping places are of great urbanistic interest for the redesign of public space in terms of livability. The data-set provides explorative pedestrian mobility in an urban microscopic level. It contains the raw data in .gpx format (an unique file for each trajectory/group). We also share processed records with specific filtering and processing (in .csv format) and also the location and the duration of the stops to perform the different actions (also in .csv format). We finally share the sociodemographic data that the participants shared before recording the trajectory (in .csv format). Citizen science practices were employed during the whole research process (co-design, crowd-sourced protocols for the experiment, collective data interpretation and policy recommendations). |
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