Artificial dataset of addresses of COVID-19 cases in Paris. The dataset was created to test geomasking techniques to be used on the real data collected by the French health administration. The dataset was used in the paper "Geographically Masking Addresses to Study COVID-19 Clusters" by Walid Houfaf-Khoufaf and Guillaume Touya. The dataset contains the following files: roads_paris_IGN.shp contains the road lines from IGN France in Paris; buildings_paris_IGN.shp contains the building polygons from IGN France in Paris (useful to aggregate points to building groups); faces.shp contains the blocks built from the roads (useful to aggregate points to blocks); ban_75.shp contains all the address points in Paris from the open BAN database. a...
International audiencePREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is cur...
An increasing number of institutions, acting at different scales and within different sectors, creat...
This is empirical dataset from the paper "The impact of human mobility networks on the global spread...
International audienceThe spatial analysis of health data usually raises geoprivacy issues. Due to t...
International audienceBackground: With more than 160 000 confirmed COVID-19 cases and about 30 000 d...
International audienceMost of the people infected in Morocco are triggered by the outbreak of COVID-...
To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-sp...
The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health autho...
Copyright © 2014 Paul A. Zandbergen.This is an open access article distributed under the Creative Co...
Background: Health professionals and authorities strive to cope with heterogeneous data, services, a...
. Machine Learning methods have been used to combat COVID-19 since the pandemic has started in year...
International audienceThis article presents a dataset called Paris-Lille-3D. This dataset is compose...
Public health datasets increasingly use geographic identifiers such as an individual’s address. Geoc...
International audiencePREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is cur...
An increasing number of institutions, acting at different scales and within different sectors, creat...
This is empirical dataset from the paper "The impact of human mobility networks on the global spread...
International audienceThe spatial analysis of health data usually raises geoprivacy issues. Due to t...
International audienceBackground: With more than 160 000 confirmed COVID-19 cases and about 30 000 d...
International audienceMost of the people infected in Morocco are triggered by the outbreak of COVID-...
To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-sp...
The unprecedented COVID-19 pandemic is showing dramatic impact across the world. Public health autho...
Copyright © 2014 Paul A. Zandbergen.This is an open access article distributed under the Creative Co...
Background: Health professionals and authorities strive to cope with heterogeneous data, services, a...
. Machine Learning methods have been used to combat COVID-19 since the pandemic has started in year...
International audienceThis article presents a dataset called Paris-Lille-3D. This dataset is compose...
Public health datasets increasingly use geographic identifiers such as an individual’s address. Geoc...
International audiencePREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is cur...
An increasing number of institutions, acting at different scales and within different sectors, creat...
This is empirical dataset from the paper "The impact of human mobility networks on the global spread...