ChildsPlayAccessibility data repository: spatial data underlying the conference paper "Easy as child’s play? Co-designing a network-based metric for children’s access to play space"

DOI:10.4121/0ec69d2a-d966-4dcd-a415-f05d756636d6.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/0ec69d2a-d966-4dcd-a415-f05d756636d6
Datacite citation style:
Teeuwen, Roos; Psyllidis, Achilleas (2023): ChildsPlayAccessibility data repository: spatial data underlying the conference paper "Easy as child’s play? Co-designing a network-based metric for children’s access to play space". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0ec69d2a-d966-4dcd-a415-f05d756636d6.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Delft University of Technology logo

Usage statistics

2127
views
123
downloads

Geolocation

Utrecht (The Netherlands), Milan (Italy) and Ljubljana (Slovenia)

Time coverage

2022

These spatial data contains potential barriers (such as roads, railways, and large greenspaces) and attractive places (such as playgrounds, schoolyards, and small parks) to children's unsupervised outdoor play in urban environments for three urban environments: Utrecht, The Netherlands; Milan, Italy; and Ljubljana, Slovenia. These data illustrate the implementations of the child's play accessibility metric, that was co-designed by the authors together with experts on children's health and the urban environment. The spatial data that was used during the co-design process is also part of this repository. 

History

  • 2023-03-21 first online, published, posted

Publisher

4TU.ResearchData

Format

GeoJSON and other geographical formats

Funding

  • Early Environmental quality and life-course mental health effects (grant code 874724) [more info...] European Commission

Organizations

TU Delft, Faculty of Industrial Design Engineering, Department of Human-Centred Artificial Intelligence

DATA

Files (1)

  • 88,180,547 bytesMD5:ad4fcbb48cbf25e78b8705091bb34a48data.zip