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Linked Data and SDI: The case on Web geoprocessing workflows

发布日期:2016-11-30 23:13:20 阅读次数:[1703]次 作者:

核心提示:来源出版物: ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

作者: Yue, P (Yue, Peng); Guo, X (Guo, Xia); Zhang, MD (Zhang, Mingda); Jiang, LC (Jiang, Liangcun); Zhai, X (Zhai, Xi)
来源出版物: ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING  卷: 114  页: 245-257  DOI: 10.1016/j.isprsjprs.2015.11.009  出版年: APR 2016
摘要: Linked Data transforms traditional ways of structuring, publishing, discovering, accessing, and integrating data. The advantages of Linked Data, including the common data model, standardized data access mechanism, and link-based data discovery, allow effective sharing and discovery of geospatial resources in Spatial Data Infrastructures (SDI). Web geoprocessing workflows have been widely used in SDI to support distributed geoprocessing. Geospatial data and services are discovered from SDI and chained as geoprocessing workflows. Workflow results can be published as new resources in SDI. The whole process could be improved by the Linked Data approach, so that sensors, observations, data, services, workflows, and provenance can be linked and published into the Web of Data. This paper explores the integration of Linked Data and Web geoprocessing workflows by discovering geospatial resources in the Web of Data to build geoprocessing workflows. It adopts the Linked Data approach to publish geospatial data including in-situ observations and satellite images, as well as geospatial Web services. The workflow results, including data products and processing steps, are also exposed as Linked Data in turn for tracing provenance. The results not only support semantic discovery and integration of heterogeneous geospatial resources, but also provide transparency in data sharing and processing. The approach is implemented as extensions to an existing geoprocessing workflow tool, GeoJModelBuilder, to illustrate its applicability. (C) 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.


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