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Data Commons is using AI to make the world’s public data more accessible and helpful

Google Paper on Data Commons, September 12, 2023: “Publicly available data from open sources (e.g., United States Census Bureau (Census) [1], World Health Organization (WHO) [2], Intergovernmental Panel on Climate Change (IPCC) [3]) are vital resources for policy makers, students and researchers across different disciplines. Combining data from different sources requires the user to reconcile the differences in schemas, formats, assumptions, and more. This data wrangling is time consuming, tedious and needs to be repeated by every user of the data. Our goal with Data Commons (DC) is to help make public data accessible and useful to those who want to understand this data and use it to solve societal challenges and opportunities. We do the data processing and make the processed data widely available via standard schemas and Cloud APIs. Data Commons is a distributed network of sites that publish data in a common schema and interoperate using the Data Commons APIs. Data from different Data Commons can be ‘joined’ easily. The aggregate of these Data Commons can be viewed as a single Knowledge Graph. This Knowledge Graph can then be searched over using Natural Language questions utilizing advances in Large Language Models. This paper describes the architecture of Data Commons, some of the major deployments and highlights directions for future work.”

Data Sources Data in the Data Commons Graph comes from a variety of sources, each of which often includes multiple surveys. Some sources/surveys include a very large number of variables, some of which might not yet have been imported into Data Commons. The sources have been grouped by category and are listed alphabetically within each category.

  1. Agriculture
  2. Biomedical
  3. Crime
  4. Demographics
  5. Economy
  6. Education
  7. Energy
  8. Environment
  9. Health
  10. Housing
  11. We also maintain a list of upcoming data imports

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