Selling Something You Cannot Own: Data Licensing, Database Rights, and the Contracts That Substitute for Property
By Casey Scott McKay ·
Data is the asset most often licensed and least often owned, and the gap between commercial expectation and legal reality is where data deals go wrong. This article explains what rights actually subsist in a dataset - thin compilation copyright after Feist, trade secret protection where secrecy holds, no US sui generis database right, and contract doing most of the work. It then works the terms that substitute for property: scope, purpose limitation, derived data, and the aggregation carve-outs that determine whether a licensee can build anything durable. It covers provenance and the rights-to-grant question that diligence turns on, privacy and regulatory flow-down, the scraping cases and what access controls actually achieve, and the exit obligations that decide what survives termination.
IP and Technology > Information Technology | Article | Published 2 March 2025 - Updated 17 June 2026 | Casey Scott McKay - marksy.us
Summary. Data is the asset most often licensed and least often owned, and the gap between commercial expectation and legal reality is where data deals go wrong. This article explains what rights actually subsist in a dataset — thin compilation copyright after Feist, trade secret protection where secrecy holds, no US sui generis database right, and contract doing most of the work. It then works the terms that substitute for property: scope, purpose limitation, derived data, and the aggregation carve-outs that determine whether a licensee can build anything durable. It covers provenance and the rights-to-grant question that diligence turns on, privacy and regulatory flow-down, the scraping cases and what access controls actually achieve, and the exit obligations that decide what survives termination.
Keywords: data licensing · database rights · Feist originality · compilation copyright · sui generis database right · trade secret in data · contract as substitute for property · terms of use enforcement · derived data · aggregated statistics · de-identification · privacy flow-down · purpose limitation · data provenance · scraping and access controls · Computer Fraud and Abuse Act · Van Buren · hiQ v LinkedIn · model training rights · exit and deletion obligations
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