The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homogeneous environment. Extracting high-level information and knowledge from such datasets to support decision making undoubtedly requires a relatively sophisticated methodology to achieve the desired results. A variety of spatial data mining techniques have been developed to extract knowledge from spatial data, which work well on centralized systems. However, applying them to distributed data in SDI to extract knowledge has remained a challenge. This paper proposes a creative solution, based on distributed computing and geospatial web service technologies for knowledge extraction in an SDI environment. The proposed approach is called Knowledge Discovery Web Service (KDWS), which can be used as a layer on top of SDIs to provide spatial data users and decision makers with the possibility of extracting knowledge from massive heterogeneous spatial data in SDIs. By proposing and testing a system architecture for KDWS, this study contributes to perform spatial data mining techniques as a service-oriented framework on top of SDIs for knowledge discovery. We implemented and tested spatial clustering, classification, and association rule mining in an interoperable environment. In addition to interface implementation, a prototype web-based system was designed for extracting knowledge from real geodemographic data in the city of Tehran. The proposed solution allows a dynamic, easier, and much faster procedure to extract knowledge from spatial data.

中文翻译：

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用于空间数据基础架构的知识发现Web服务

地理传感器，人员和组织收集的地理空间数据的大小，数量，种类和速度都在迅速增加。空间数据基础结构（SDI）正在进行中，以促进在分布式均匀环境中共享存储的数据。从此类数据集中提取高级信息和知识以支持决策无疑需要一种相对复杂的方法来实现所需的结果。已经开发了多种空间数据挖掘技术来从空间数据中提取知识，这些技术在集中式系统上运行良好。但是，将它们应用于SDI中的分布式数据以提取知识仍然是一个挑战。本文提出了一种创新的解决方案，该解决方案基于分布式计算和地理空间Web服务技术，用于SDI环境中的知识提取。所提出的方法称为知识发现Web服务（KDWS），可以用作SDI之上的一层，为空间数据用户和决策者提供从SDI中的大量异构空间数据中提取知识的可能性。通过提出和测试KDWS的系统体系结构，本研究有助于执行空间数据挖掘技术，将其作为基于服务的框架在SDI之上进行知识发现。我们在可互操作的环境中实施并测试了空间聚类，分类和关联规则挖掘。除了实现界面之外，还设计了一个基于Web的原型系统，用于从德黑兰市的真实地理人口统计数据中提取知识。所提出的解决方案允许动态，更容易且更快得多的过程从空间数据中提取知识。