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Data intermediaries may foster data reuse, thus facilitating efficiency and innovation. However, research on the subject suffers from terminological inconsistency and vagueness, making it difficult to convey to policymakers when data governance succeeds and when data sharing requires regulatory intervention. The paper describes what distinguishes data intermediaries from other data governance models. Building on research on intellectual property governance, we identify two distinct types of data intermediaries, data clearinghouses and data pools. We also discover several governance models that are specific to data and not present in the context of intellectual property. We conclude that the use of more refined terminology to describe data intermediaries will facilitate more accurate research and informed policy-making on data reuse.
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