Data Commons has benefited greatly from our collaborations with different government organizations and academic institutions and is looking to expand the set of collaborative projects. In particular, we are looking for partners to:

Add data: Contribute data to Data Commons.
Create new curriculum: Use Data Commons in data science and machine learning courses.
Create tools: Build new tools or applications that bring the data in Data Commons to new categories of users.
Share analyses: Use Data Commons to build models and share interesting insights.
Write documentation

Data Commons welcomes patches and contributions to this project from everyone, new or experienced!

Ways to contribute

Add data

We welcome contributions of public data to the Data Commons knowledge graph. Data added will be accessible via Data Commons tools and APIs. We’ve bootstrapped the knowledge graph with these datasets from US Census, World Bank, CDC, NOAA, NASA, etc. However, Data Commons is meant to be for the community, by the community. We’re excited to work with you to make public data accessible to everyone. If you are interested in importing your data to Data Commons, please file a data request in our issue tracker. You can see a list of existing requests here.

Create new curriculum

Data Commons allows for easy acess to real data that can enrich the experience of students and instructors in educational contexts. We’re posting template data science assignments to assist educators with integrating real data into their courses on the courseware page. If you use Data Commons for your classes, have courseware to share, or find any of this material helpful, we want to hear about it! Please fill out this form.

Create a new tool

Data Commons welcomes the development of new tools that make the data on Data Commons more accessible to end users. We have an extensive REST API that can be used to power applications on top of our data. If you would like to build a new tool, contact the team through this form or create a PR in the Data Commons tools repo.

Example analyses are available on the tutorials page. To add your analysis on that page, open a PR in the Data Commons documentation repo with the title of the analysis and links to its Colab notebook and Github raw .ipynb file.

Update documentation

Data Commons maintains its documentation website at https://docs.datacommons.org. You can submit a PR to update the project’s documentation at https://github.com/datacommonsorg/docsite/pulls.

Get started

Sign the Contributor License Agreement (CLA)

Contributions to this project must be accompanied by a Contributor License Agreement. You (or your employer) retain the copyright to your contribution; this simply gives us permission to use and redistribute your contributions as part of the project. Head over to https://cla.developers.google.com/ to see your current agreements on file or to sign a new one. You generally only need to submit a CLA once, so if you’ve already submitted one (even if it was for a different project), you probably don’t need to do it again.

Become familiar with the project

You can read about Data Commons concepts and explore existing data and tools on datacommons.org.

All submissions, including submissions by project members, require review. Data Commons uses GitHub pull requests for this purpose. Consult GitHub Help for more information on using pull requests. This project follows Google’s code style guide, documentation style guide, and open source community guidelines.

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Contribute to Data Commons!