Fragmentation of production across national boundaries results in global supply chains. To govern effectively in this type of economy requires a combination of public data with private initiatives (from business, banks and NGOs). But basically, there are three major challenges to that: a) data comprises distributed and isolated data sets; b) analytics requires models to be trained across these independent data sets; and c) data sovereignty and specific privacy legislations make it difficult to collect, share and analyze data. Our research proposes three complementary paths to overcome these problems: 1) the use of federated learning; 2) the creation of open data catalogues; and 3) the design of distributed ledger technologies., Paper presented at the Symposium on Data Analytics and anti-corruption that was co-hosted by the World Bank and the Korea Development Institute School of Public Policy and Management on October 25-28. The four-day event was launched with a Call for Papers, 26 of which were selected for the Symposium. The papers presented covered four thematic areas: 1.- New data-driven approaches to detecting and measuring corruption; 2.- Using new data sources and methods to measure the impacts of corruption 3.- Using open data to assess the effectiveness of anti-corruption tools, policies, and interventions 4.- Contributing new knowledge on data access, quality, and privacy issues. This paper was presented in Panel 3B, on October 26, from 10:45 AM to 12:00 PM, EDT. The recording of the presentation is on https://youtu.be/UxbP6Y3DhwQ?t=10010, {"references":["Deloitte, Center for Government Insights, Jason Killmeyer, Mark White, and Bruce Chew. 2017. 'Will Blockchain Transform the Public Sector?' https://www2.deloitte.com/content/dam/insights/us/articles/4185_blockchain-public-sector/DUP_will-blockchain-transform-public-sector.pdf. 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