The Advent of Data Commons

Stanford Consulting

Data is all around us. Governments, researchers, and institutions collect data to inform policy and practices. Much of this data, however, is disconnected and inaccessible for the general public and other researchers. 

An emerging solution to this problem is the creation of data commons: cloud-based platforms that allows members to contribute, analyze, and merge different datasets. These data commons allow researchers to browse existing data in a field and make use of it in their own studies. 

Many public and private organizations have created data commons to conglomerate data. For instance, Federal Reserve Economic Data, commonly known as FRED, is a database on inflation, unemployment, and other macroeconomic indicators. The National Cancer Institute has also created a Genomic Data Commons to share high quality research that will improve precision medicine. Google Data Commons is another initiative that transcends fields such as climate research, demographic data, economic trends, and more. 

As data commons expand their reach and user bases, we have identified some key considerations for stakeholders in the field to prioritize: 

  1. Clear Governance: A well-defined set of rules and guidelines for data contribution, access, and usage forms the backbone of a responsible commons. These guidelines should be informed by ethical considerations and relevant legal frameworks to ensure accountability.
  2. Robust Infrastructure: Secure storage, access-control mechanisms like role-based access, and robust data management tools are essential to maintain data integrity, privacy, and usability.
  3. Metadata Standards: Evolving metadata practices are crucial for efficient data search, discovery, and understanding, especially since machine learning and natural language processing technologies are advancing at such a quick rate.
  4. Interoperability: Connecting with other data platforms and repositories fosters wider collaboration and data exchange between government agencies, the private sector, and citizens. For instance, data commons can routinely update data from their sources or use APIs to allow programmers to access data. Absent such interoperability, data may remain in silos and inaccessible.
  5. Transparency: Clear communication about data sources, methodologies, and limitations builds trust and encourages responsible use. Complete transparency will encourage participation from citizens and private entities, and uphold critical ethical principles. 
  6. User Support: Responsive mechanisms to address user needs and questions, like dedicated help desks or user forums, promote engagement and effective data utilization.

Additional Resources to Learn more about Data Commons

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