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With the evolution and widespread adoption of contemporary information technologies, data has taken an increasingly central role in almost all areas of human activity. While on one hand this protagonism of data brings significant benefits for the individuals and organizations, on the other hand it is accompanied by a number of challenges. In the domain of Big Data, Linked Data and Semantic Web, common examples of these challenges include scale, performance, availability, security, diversity, complexity, semantics, manageability and findability. In January 2014, a group of stakeholders involved in research data came together to debate how to further enhance infrastructures to support a data ecosystem that promotes data interoperability and reuse. The main outcome of this meeting was the definition of the so called FAIR Data guiding principles aimed at publishing data in a format that is Findable, Accessible, Interoperable and Reusable by both machines and human users. Since the seminal meeting, the FAIR Data initiative has grown with an increasing number of participant organizations and involved projects. In this chapter we report the progress in the development of one of the components of the FAIR Data infrastructure, the FAIR Data Point (FDP). The FDP is software that, from one side, allows data owners to expose datasets in compliance with the FAIR principles and, from another side, allows data users to discover information about the available datasets and, ultimately, access the underlying data records.