Semagrow is a federated query processor that allows combining, cross-indexing and, in general, making the best out of all public data, regardless of their size, update rate, and schema. Semagrow offers a single SPARQL endpoint that serves data from remote data sources and that hides from client applications heterogeneity in both form (federating non-SPARQL endpoints) and meaning (transparently mapping queries and query results between vocabularies).
Semagrow has been used to integrate diverse datasets in multiple domains and applications. Among others, meteorological, land-usage, water availablity, and crops data for food security; meteorological, GIS, and dispersion modelling data for risk estimation, biology and pharmacology datasets for pharmacological research.
The official Semagrow repository can be found here: https://github.com/semagrow/
The official Docker images of Semagrow can be found here: https://hub.docker.com/r/semagrow/
The homepage of Semagrow can be found here: http://semagrow.github.io/