A Transformation of the RDF Mapping Language into a High-Level Data Analysis Language for Execution in a Distributed Computing Environment

Nowadays scientific data should be FAIR that are Findable, Accessible, Interoperable and Reusable. Reference implementation of FAIR data management principles proposed recently considers RDF as unifying data model and RDF Mapping Language (RML) as the basic language for data integration. This paper is aimed at development of methods and tools for scalable data integration in the frame of this architecture. A mapping from RML into a high-level data analysis language Pig Latin that runs on Hadoop is considered. The mapping is implemented using model transformation technologies. These allows to execute RML programs in the Hadoop distributed computing environment. According to the experimental evaluation RML implementation developed scales w.r.t. data volume and outperforms related implementations.