This is a collaborative effort to establish a common data set about Swiss public medical infrastructure, where the community can contribute and manage data in a moderated way. Our goal is to improve the transparency and efficiency of data exchange about basic indicators, expanding on the existing available open government data.
This project was started at the Monitoring COVID-19 effects (#covid19mon) hackathon. Visit our challenge page for further details and tasks, some of which are in our current notes and backed up here. Please suggest additional data sources and ideas in the issue tracker.
:package: View the crowdsourced Data Package and OGD Data Schema to check the data baseline.
:mag: Use our Online Form to submit individual data points or corrections.
:floppy_disk: Visit the Issue Tracker to find out how you could contribute to automation & validation.
:grapes: Explore visualizations (ETH) and models (neherlab, plotti) that use this data.
:person_with_pouting_face: Join our Team Chat if you have any other questions or suggestions.
:construction: This README is very much Work In Progress. :construction:
There is an initial Data Package which can be previewed here.
Please see the data folder to see all the datasets that we are working on.
Instructions: Accessible data files (ideally in simple data formats such as CSV, JSON and GeoJSON), as well as the raw data, are placed in the
datafolder. In this section you should mention the files and formats included. It is good to suggest purposes for this data, such as example applications or use cases. Include any relevant background, contact points, and links that may help people to use this data. You can find examples of this at datahub.io or github.com/datasets, and further tips at frictionlessdata.io and datahub.io.
Details of what data we are using and how we are preparing it can be found in our notes.
Instructions: describe here where you obtained the data, how it was created, where and how it was extracted, and any transformation steps that took place during publication. Link to the sources, as well as to any tools that were used. If you used any scripts to extract and convert the data, add them to a
scriptfolder in your repository.
The licensing terms of this dataset have not yet been established. If you intend to use these data in a public or commercial product, check with each of the data sources for any specific restrictions.
This Data Package is made available by its maintainers under the Public Domain Dedication and License v1.0, a copy of the full text of which is in LICENSE.md.