White Paper Federated Data Systems

The document explores federated data systems as a solution to the tension between data protection and innovation. It details how these systems use APIs to allow computation to move to the data, keeping sensitive information localized while enabling global insights. The paper identifies governance, trust, and technical standardization as primary hurdles and suggests the use of real-world pilots and open standards to advance the field.

• Federated data systems address the conflict between data protection and innovation by allowing data to remain localized while enabling authorized queries to be sent between disparate repositories. This architecture ensures that "the data never leaves the organization that holds it," and only the computed answers are returned to the user.
• The technical foundation of federated systems relies on application programming interfaces (APIs) and shared technology architectures. APIs allow for the enforcement of local governance policies and legal requirements, ensuring that "governance control to reside with each local entity in the federation."
• Genomic data presents unique challenges for federation because it is highly unique and can reveal information about an individual's relatives. This creates a risk where "it may become possible to reidentify that person if enough additional identifiers can be matched with the genomic information."
• The document identifies several operational examples of federated systems: CanDIG in Canada for health data analysis, the Open Algorithms (OPAL) project for private-sector data in Colombia and Senegal, and evaluations by the office of European Statistics for Trusted Smart Statistics.
• Significant non-technical barriers to the adoption of federated systems include the difficulty of gaining stakeholder agreement on shared goals, defining data access rights, establishing financial models, and managing the threshold for members to enter or exit a federation.
• To advance federated systems, the paper recommends the development of open technical standards, the creation of agile governance frameworks, the use of "sandboxes" for lightweight experimentation, and the adoption of "dynamic consent" to allow individuals to modify their data-use preferences over time.

APA

World Economic Forum (2019). White Paper Federated Data Systems. http://www3.weforum.org/docs/WEF_Federated_Data_Systems_2019.pdf

Chicago

World Economic Forum. White Paper Federated Data Systems. 2019. http://www3.weforum.org/docs/WEF_Federated_Data_Systems_2019.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=White Paper Federated Data Systems |date=July 2019 |url=http://www3.weforum.org/docs/WEF_Federated_Data_Systems_2019.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2019white, author = {{World Economic Forum}}, title = {{White Paper Federated Data Systems}}, institution = {World Economic Forum}, year = {2019}, month = jul, url = {http://www3.weforum.org/docs/WEF_Federated_Data_Systems_2019.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }