In this paper, we describe the approach of the Earth, Life and Semantic Web (ELSEWeb) project that facilitates the discovery and transformation of Earth observation data sources for the creation of species distribution models (data-to-model) transformations. ELSEWeb automates the discovery and processing of voluminous, heterogeneous satellite imagery and other geospatial data available at the Earth Data Analysis Center to be included in Lifemapper Species Distribution models by using AI knowledge representation and reasoning techniques developed by the Semantic Web community. The realization of the ELSEWeb semantic infrastructure provides the possibility of combinatoric explosions of scientific results, automatically generated by orchestrations of data mash-ups and service composition. We report on the key elements that contributed to the ELSEWeb project and the role of automated reasoning in streamlining the Species Distribution Model generation and execution.