In the Big Data era, both the academic community and industry agree that a crucial point to obtain the maximum benefits from the explosive data growth is integrating information from different sources, and also combining methodologies to analyze and process it. For this reason, sharing data so that third parties can build new applications or services based on it is nowadays a trend. Although most data sharing initiatives are based on public data, the ability to reuse data generated by private companies is starting to gain importance as some of them (such as Google, Twitter, BBC or New York Times) are providing access to part of their data. However, current solutions for sharing data with third parties are not fully convenient to either or both data owners and data consumers. Therefore we present dataClay, a distributed data store designed to share data with external players in a secure and flexible way based on the concepts of identity and encapsulation. We also prove that dataClay is comparable in terms of performance with trendy NoSQL technologies while providing extra functionality, and resolves impedance mismatch issues based on the Object Oriented paradigm for data representation.This work has been supported by the Spanish Government (grant SEV2015-0493 of the Severo Ochoa Program), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316) and by Generalitat de Catalunya (contract 2014-SGR-1051). Special thanks go to Dr. Oscar Romero (Universitat Politècnica de Catalunya) for providing helpful feedback on the paper.Peer ReviewedPostprint (published version

Abstract-Current Data as a Service solutions present a lack of flexibility in terms of allowing users to customize the underlying data models by including new concepts or functionalities. Data providers either publish global APIs to make data available, or "sell" and transfer data to clients so they can do whatever they want with it. Thereby, collaboration and B2B becomes limited and sometimes is not even feasible. Our technology implements the necessary mechanisms for data providers to enable their clients to enrich data models both with additional concepts and with new methods that can be executed and, in turn, published as new services.