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How the DOC Is Using Blockchain to Revolutionize U.S. Economic Data

Quick Highlights DOC to publish July 2025 GDP data on multiple blockchains. Coinbase, Gemini, and Kraken facilitate public data access. Chainlink and Pyth oracles distribute government macroeconomic data. U.S. GDP Data Set to Go Blockchain The U.S. Department of Commerce (DOC) will begin publishing real gross domestic product (GDP) data on the blockchain, beginning with the July 2025 release. This marks the first time a federal agency has made economic data publicly available in a blockchain format, combining transparency, security, and innovation. Specifically, the DOC has already released the official hash of its 2025 quarterly GDP data on nine blockchains: Bitcoin, Ethereum, Solana, TRON, Stellar, Avalanche, Arbitrum One, Polygon PoS, and Optimism. The data was also distributed via Pyth and Chainlink oracles, while cryptocurrency exchanges Coinbase, Gemini, and Kraken helped release the information. Going forward, the agency plans to expand the scope of future datasets, including GDP, by engaging additional blockchains, oracles, and exchanges. Innovation and Federal Data Security “This is the first time a federal agency has published economic statistical data like this on the blockchain, and the latest way the Department is utilizing innovative technology to protect federal data and promote public use,” the DOC press release said. The initiative also builds on previous efforts by the administration of former U.S. President Donald Trump to position the U.S. as a global blockchain leader. Collaboration With Chainlink and Oracles Chainlink and the U.S. Department of Commerce have partnered to provide access to U.S. government macroeconomic data from the Bureau of Economic Analysis. This collaboration ensures that GDP and other critical datasets are both secure and widely accessible, while enabling seamless distribution to the public and private sectors. With blockchain, users can verify data authenticity independently, making the system more transparent and resilient than traditional publication methods.
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