Interpreting Heterogeneous Geospatial Data Using Semantic Web Technologies

被引:9
|
作者
Homburg, Timo [1 ]
Prudhomme, Claire [1 ]
Wuerriehausen, Falk [1 ]
Karmacharya, Ashish [1 ]
Boochs, Frank [1 ]
Roxin, Ana [2 ]
Cruz, Christophe [2 ]
机构
[1] Mainz Univ Appl Sci, Lucy Hillebrand Str 2, D-55128 Mainz, Germany
[2] Univ Bourgogne, 9 Ave Alain Savary, F-21000 Dijon, France
关键词
Heterogeneity; Interoperability; SDI; CIP; GeoSPARQL; R2RML; Semantification;
D O I
10.1007/978-3-319-42111-7_19
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paper presents work on implementation of semantic technologies within a geospatial environment to provide a common base for further semantic interpretation. The work adds on the current works in similar areas where priorities are more on spatial data integration. We assert that having a common unified semantic view on heterogeneous datasets provides a dimension that allows us to extend beyond conventional concepts of searchability, reusability, composability and interoperability of digital geospatial data. It provides contextual understanding on geodata that will enhance effective interpretations through possible reasoning capabilities. We highlight this through use cases in disaster management and planned land use that are significantly different. This paper illustrates the work that firstly follows existing Semantic Web standards when dealing with vector geodata and secondly extends current standards when dealing with raster geodata and more advanced geospatial operations.
引用
收藏
页码:240 / 255
页数:16
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