Autonomous Spatial Data Source 自治空间数据源
Multi-source spatial Data 多源空间数据
multi-source heterogeneous spatial data 多源异构空间数据
Seamless Integration of Multi-source Spatial-data 多源空间数据无缝集成
Fusion of Multi-source Spatial Data 多源空间数据的融合
SOURCE SPATIAL DATA 上一篇论文
Multi-source spatial data integration 多源空间数据集成
Integration of muti-source spatial data 多源空间数据的整合
The traditional researches of spatial data integration focus on the phrasing and pattern layers, which have shortage in the semantic information integration of the different geographic spatial data source and cause some difficulties in data share.
传统的空间数据集成研究侧重于语法和模式层次,在集成不同地理空间数据源的语义方面有所不足,导致了数据共享的困难。
参考来源 - 基于地理本体的空间数据集成研究·2,447,543篇论文数据，部分数据来源于NoteExpress
This article does not cover how to set up a nickname, as that is a well-documented, general (non-spatial) process; I simply assume that you have access to the source data, whether it is local or not.
本文不讨论如何设置昵称，因为这是具有丰富文档可供参考的一般性(非空间)过程；我假设您能够访问源数据，无论源数据是否是本地的。
Besides, since it is open source, it is much easier to add conditions to handle specific scenarios like spatial data.
此外，由于PetaPoco是开源项目，因此添加条件来处理如空间数据等特定情况会很容易。
Analyzing the source of spatial data and improving the quality of spatial data are the precondition of building GIS.
分析空间数据来源、提高空间数据质量是建立地理信息系统的前提。
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