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The Web of Data (WoD) is to computers what the traditional Web is to humans. The goal is to expose data in a semantic format such that machines can easily find the information they are looking for. If implemented properly, a semantic search would lead to the desired results much faster than using a traditional search engine. However, a big practical challenge is the adoption of WoD technologies (Antoniou and van Harmelen, 2004). In particular, the majority of data is not available in a suitable WoD format. The primary reason for this is a lack of incentives for data providers: the WoD is usually queried via algorithms rather than browsed by people and thus, advertising, the main source of income for search engines on the traditional web, does not work. It is of course possible to directly charge users to search through high-quality data. For example, Bloomberg, Lexis-Nexis, and Thomson Reuters charge customers high fees for accessing their data. However, none of these companies provide the means to join multiple data sets, thereby forgoing the complementarities the WoD would enable. To address this shortcoming, we suggest using a market which allows buyers to benefit from complementary data sources while providing incentives to sellers to adopt WoD technologies. Concretely, we propose to use a double auction, designed to provide market participants with good incentives to reveal their values and costs such that we can make (approximately) efficient allocations. Interestingly, in our domain, it is non-trivial to find a payment rule that satisfies the participation constraint (all participants have non-negative utility) and the budget-balance …