2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)
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Abstract

There is a tremendous number of geospatial data becoming available and there are numerous methods for getting access to geospatial sources. However, diverse geospatial data sources lead to various extracting ways. Users without adequate background knowledge are unable to fully exploit the growing amount of geospatial data. Our work provides users with a uniform interaction paradigm to tackle the variant retrieval problems in a universal way. Unifying the retrieval methods requires the ability to invoke processing algorithms by a uniform interaction paradigm. Our approach, implemented in a tool called Karma, encapsulates these algorithms as Web Services. As different sources present diverse non-semantic geospatial data, users cannot fully understand the extracted geospatial data. We have defined a general ontology to align and semantify the retrieved data. In addition, we present the principles underlying our approach, and several running examples are given to demonstrate the feasibility and effectiveness of our prototype.

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