Auditing Remote Sensing Data Using Geospatial Provenance.

Auditing Remote Sensing (RS) data can be a tough task due to the huge heterogeneity of RS data and geoprocessing tools available. In this sense, provenance information, part of the metadata that describes "what", "when", "who", "how" and "where" have generated a particular geospatial data, can be very useful. This contribution focuses on how to query provenance information in order to receive back data sources and geoprocessing tools that have participated in the generation of datasets in a catalog. This way, queries over data provenance can be used to infer data quality, trace errors sources, trust and authority of a geospatial information.