|Data marketplaces are the digital platform for data buyers and data sellers to trade information as valuable products or items. The expectation taken for granted from the users of a data marketplace is the truth of the exchanged information. However, the trade of factual data also means the marketable product is no longer unique but a series of replicas. If every user within the data marketplace owns the same information, this data eventually becomes valueless. There are specific instances where the traded products are sought to be always unique, such as predictions or digital art. This paper presents Echo State Networks (ESNs) in data marketplaces that map tradeable data into higher dimensional spaces via the dynamics of a fixed and non-linear reservoir. The reservoir generates unique tradeable data products that can not be replicated, therefore ensuring its exclusivity and commercial value. The validation results show that ESNs can also be applied to generate random tradeable products on different dimensional spaces. Specifically, the reservoir with its associated neural perturbation emulates a digital artist that generates unique and exclusive content based on 2D functions and 3D images.|
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