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Data generated by scientific research enables further advancement in science through reanalyses and pooling of data for novel analyses. With the increasing amounts of scientific data generated by biomedical research providing researchers with more data than they have ever had access to, finding the data matching the researchers' requirements continues to be a major challenge and will only grow more challenging as more data is produced and shared. In this paper, we introduce a horizontally scalable distributed extract-transform-load system to tackle scientific data aggregation, transformation and enhancement for scientific data discovery and retrieval. We also introduce a data transformation language for biomedical curators allowing for the transformation and combination of data/metadata from heterogeneous data sources. Applicability of the system for scientific data is illustrated in biomedical and earth science domains.

Foundry: a message-oriented, horizontally scalable ETL system for scientific data integration and enhancement