Semantic integration of geospatial data from earth observations

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Abstract

We propose an approach to semantically enrich metadata records of satellite imagery with external data. As a result we are able the identify relevant images using a larger set of matching criteria. Conventional methods for annotating data sets are usually based on metadata records (with attributes such as title, provider, access mode, and spatiotemporal characteristics), which offer a narrow view of the world. Enriching metadata with contextual information (e.g., the region depicted in the image has been recently affected by extreme weather) requires formalizing spatio-temporal relationships between metadata records and external data sources. Semantic technologies play a key role in such scenarios by providing an infrastructure based on RDF and ontologies.

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Arenas, H., Aussenac-Gilles, N., Comparot, C., & Trojahn, C. (2017). Semantic integration of geospatial data from earth observations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10180 LNAI, pp. 97–100). Springer Verlag. https://doi.org/10.1007/978-3-319-58694-6_8

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