Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study

Cancer Epidemiol Biomarkers Prev. 2020 Apr;29(4):777-786. doi: 10.1158/1055-9965.EPI-19-0842. Epub 2020 Feb 12.


Background: Large-scale cancer epidemiology cohorts (CEC) have successfully collected, analyzed, and shared patient-reported data for years. CECs increasingly need to make their data more findable, accessible, interoperable, and reusable, or FAIR. How CECs should approach this transformation is unclear.

Methods: The California Teachers Study (CTS) is an observational CEC of 133,477 participants followed since 1995-1996. In 2014, we began updating our data storage, management, analysis, and sharing strategy. With the San Diego Supercomputer Center, we deployed a new infrastructure based on a data warehouse to integrate and manage data and a secure and shared workspace with documentation, software, and analytic tools that facilitate collaboration and accelerate analyses.

Results: Our new CTS infrastructure includes a data warehouse and data marts, which are focused subsets from the data warehouse designed for efficiency. The secure CTS workspace utilizes a remote desktop service that operates within a Health Insurance Portability and Accountability Act (HIPAA)- and Federal Information Security Management Act (FISMA)-compliant platform. Our infrastructure offers broad access to CTS data, includes statistical analysis and data visualization software and tools, flexibly manages other key data activities (e.g., cleaning, updates, and data sharing), and will continue to evolve to advance FAIR principles.

Conclusions: Our scalable infrastructure provides the security, authorization, data model, metadata, and analytic tools needed to manage, share, and analyze CTS data in ways that are consistent with the NCI's Cancer Research Data Commons Framework.

Impact: The CTS's implementation of new infrastructure in an ongoing CEC demonstrates how population sciences can explore and embrace new cloud-based and analytics infrastructure to accelerate cancer research and translation.See all articles in this CEBP Focus section, "Modernizing Population Science."

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Big Data
  • Cloud Computing / legislation & jurisprudence*
  • Computer Security
  • Data Collection / legislation & jurisprudence
  • Data Collection / methods*
  • Data Warehousing / legislation & jurisprudence
  • Data Warehousing / methods*
  • Health Information Management / legislation & jurisprudence
  • Health Information Management / methods*
  • Health Insurance Portability and Accountability Act
  • Humans
  • Longitudinal Studies
  • Neoplasms / epidemiology*
  • Observational Studies as Topic / legislation & jurisprudence
  • Observational Studies as Topic / methods
  • Prospective Studies
  • United States