Abstract
With the development of geoscience, users are eager to obtain preferred service from geospatial information intelligently and automatically. However, the information grows rapidly while the service gets more complicated, which makes it difficult to find out the targeted information for an exact service in geospatial issues. In this paper, a novel method is proposed to promote the geospatial service from information to knowledge with spatiotemporal semantics. Both prompted and professional knowledge are further refined to be published as a service. In terms of an exact task, numerous related services are recombined to a service chain under user requirement. Finally, the proposed method is applied to monitor the environment on the Air Quality Index (AQI) and soil moisture (SM) in the Sensor Web service platform, the results of which indicate geospatial knowledge service (GKS) is more efficient to support spatial decision‐making.
Highlights
Nowadays, the geoscience issues benefit from the services of geospatial information
Queried by the keywords “the air quality of Wuhan city from 2014-09-08 14:00 to 2014-09-10 15:00” and “the soil moisture of Baoxie in Wuhan city from 2014-07-05 to 2014-07-07,” following the reasoning method introduced in Section 2.4, the air quality monitoring service of Wuhan and the soil moisture service of Baoxie were achieved, as shown in Figures 9-10
A novel method is proposed to promote the geospatial service from information to knowledge with spatiotemporal semantics
Summary
The geoscience issues benefit from the services of geospatial information. Users query the registered services on geospatial information, and the services are composited to form a service chain with the intervention from the users under a given task. The formalization requirement of geospatial information web service is strict. It highly depends on users’ manual intervention. The development of machine learning makes it possible to acquire knowledge with professional tools [4] Such methods are time-consuming and face difficulty in meeting the requirement of knowledge acquisition, while spatial data mining might precisely solve the problem. GKS automatically realizes service query, service reasoning, and service composition, and intelligently provides users with the targeted information. A novel method is proposed to promote the geospatial service from information to knowledge with spatiotemporal semantics.
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