Covid-19 Public Data Collaboration Project

This project aggregates data from various public data sources to better understand the spread and effect of covid-19. The goal is to provide a central place where data, analysis, and discussion can be conducted and shared by a global community struggling to make sense of the current public health emergency.

See the dashboard for a summary of the global data.

Getting started and working with the project

The simplest way to start is to make an account or logging in and forking the project. Then, feel free to start an interactive environment and use the hosted JupyterLab or RStudio to explore the data. A summary of the data is given below. Please please please consider contributing back cool results from your fork! If you don't know how or just need help with some of the git-heavy aspects of this, shoot us a line on Discourse or open an issue and someone will be able to help out.

The environment image allows you to work in Python or R in JupyterLab or RStudio/Shiny.

Updating your branch or fork

The data in the main master branch of this project is updated daily - how can you keep your fork or branch up-to-date? We recommend that you do not make changes to the files and directories that are automatically updated so as to avoid merge conflicts as much as possible. This includes the datasets in the data/ directory and the notebooks in notebooks/ and runs/. Especially for notebooks, the easiest way to avoid conflicts would be to simply make a new directory where you put your work.

When you are ready to pull in changes from master, you can do the following from a terminal, when working on your branch or fork:

git remote add upstream https://renkulab.io/gitlab/covid-19/covid-19-public-data.git
git fetch upstream
git merge upstream/master

This will sync your branch or fork with the latest changes from the master branch of the parent repository.

Dataset Summary

Covid-19 Data Repository JHU CSSE

This is a global Covid-19 dataset updated regularly from Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). The dashboard summarizes this data in combination with population data from the world bank.

Covid tracking crowdsourcing project

Covid tracking is a crowd-sourced dataset for US state-level data. It is updated by hand by an army of volunteers.

OpenData Zuerich

The swiss cantonal data collected by the Zürich statistical office. Parts are updated manually, others are starting to become automated.

Case data for Italy

Detailed data compiled by the Civil Protection of Italy.

Covid-19 related tweet IDs

A collection of tweet-ids related to covid-19 from https://github.com/echen102/COVID-19-TweetIDs.

General

• https://data.worldbank.org/indicator/SP.POP.TOTL
• https://worldmap.harvard.edu/data/geonode:country_centroids_az8

Derived Dataset Summary

Contributing

If you are interested in working on this project, we would love to get contributions. We would really like to collect more data sources and make them available here! Please provide ideas for data sources that are relevant to understanding covid-19.

If you want to add a new datasource yourself, see the section Adding a new data source

Data Sources to Add

See the data sources issue.

Adding a new data source

Adding a new data source is easy! To do so, in your fork or branch of the project, do the following:

• Create a renku dataset using renku dataset create [dataset name]
• Add any files or folders using renku dataset add. Looking in the commit history will provide some examples.
• Create a notebook that shows how to read and work with the dataset in the notebooks/examples folder
  • Protip: use a unique name for the notebook to avoid merge conflicts
• Add an issue to the project for any suggestions on things to do with the data