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Promoting Geospatial Service from Information to Knowledge with Spatiotemporal Semantics

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  • Jing Geng
  • Shuliang Wang
  • Wenxia Gan
  • Hanning Yuan
  • Zeqiang Chen
  • Ziqiang Yuan
  • Tianru Dai

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.

Suggested Citation

  • Jing Geng & Shuliang Wang & Wenxia Gan & Hanning Yuan & Zeqiang Chen & Ziqiang Yuan & Tianru Dai, 2019. "Promoting Geospatial Service from Information to Knowledge with Spatiotemporal Semantics," Complexity, Hindawi, vol. 2019, pages 1-14, January.
    • Handle: RePEc:hin:complx:9301420
    DOI: 10.1155/2019/9301420
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    References listed on IDEAS

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    1. Gang Tian & Jian Wang & Keqing He & Chengai Sun & Yuan Tian, 2017. "Integrating implicit feedbacks for time-aware web service recommendations," Information Systems Frontiers, Springer, vol. 19(1), pages 75-89, February.
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    Cited by:

    1. Maryam Barzegar & Abolghasem Sadeghi-Niaraki & Maryam Shakeri & Soo-Mi Choi, 2019. "An Improved Route-Finding Algorithm Using Ubiquitous Ontology-Based Experiences Modeling," Complexity, Hindawi, vol. 2019, pages 1-15, November.

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