Sharing and Analyzing Remote Sensing Observation Data for Linked Science

Presented at: 9th Extended Semantic Web Conference (ESWC2012)

by Tomi Kauppinen, Benedikt Gräler, Giovana Mira de Espindola

In order to make research settings transparent and reproducible there is a need for publishing both data and methods behind the research. In this paper our contribution is to show how large amounts of remote sensing observation data about the Brazilian Amazon Rainforest has been published as Linked Spatiotemporal Data. Moreover, we show how this data can be further accessed and analyzed using R statistical computing environment by openly available methods. This all is a contribution towards Linked Science, where not just publications, but data, methods, tools, and all scientific assets are interconnected and shared online.

Keywords: Linked Science, Linked Spatiotemporal Data, Semantic Web, Statistical Computing


Resource URI on the dog food server: http://data.semanticweb.org/conference/eswc/2012/paper/poster/347


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