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The Worldclim data set provides environmental data for 68 variables at a 30 second spatial resolution. These data are highly useful for applications such as creating species distribution models or simply viewing the environmental information for a single species record. However, searching for data with such simple criteria as “give me all environmental values at this point or within this bounding box” is surprisingly difficult because of the computational resources (mainly memory) required to answer these questions. To address these challenges, the Spatial Data Library, developed through the University of Kansas, is an open source project hosted on GitHub that provides access to Worldclim data hosted on CouchDB and Google App Engine using a simple web Application Programming Interface (API). The API supports searches that show the values of environmental variables at a single geographic point or within a bounding box. The API also supports searching for geographic locations (as grid cells) based on ranges values for environmental variables. In this talk we will describe the conceptual and technical framework used to process and store these data efficiently in a way that performs extremely well while keeping costs low.

https://github.com/eightysteele/Spatial-Data-Library