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Integrating Spatial Data Linkage and Analysis Services in a Geoportal for C hina Urban Research
Author(s) -
Zhu Xinyan,
She Bing,
Guo Wei,
Bao Shuming,
Chen Di
Publication year - 2015
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/tgis.12084
Subject(s) - geospatial analysis , computer science , geoportal , service (business) , data mining , web service , linkage (software) , data transformation , information retrieval , table (database) , web coverage service , spatial analysis , data science , world wide web , data warehouse , geography , web mapping , data web , cartography , biochemistry , chemistry , economy , gene , economics , gis and public health , remote sensing
Many geoportals are now evolving into online analytical environments, where large amounts of data and various analysis methods are integrated. These spatiotemporal data are often distributed in different databases and exist in heterogeneous forms, even when they refer to the same geospatial entities. Besides, existing open standards lack sufficient expression of the attribute semantics. Client applications or other services thus have to deal with unrelated preprocessing tasks, such as data transformation and attribute annotation, leading to potential inconsistencies. Furthermore, to build informative interfaces that guide users to quickly understand the analysis methods, an analysis service needs to explicitly model the method parameters, which are often interrelated and have rich auxiliary information. This work presents the design of the spatial data linkage and analysis services in a geoportal for C hina urban research. The spatial data linkage service aggregates multisource heterogeneous data into linked layers with flexible attribute mapping, providing client applications and services with a unified access as if querying a big table. The spatial analysis service incorporates parameter hierarchy and grouping by extending the standard WPS service, and data‐dependent validation in computation components. This platform can help researchers efficiently explore and analyze spatiotemporal data online.