面向地理问题求解的数据表达模型研究

Geographic Problem-Solving Oriented Data Representation Model

本文以地理问题求解和地理科学研究建模环境建设的需求为导向,针对面向地理问题求解建模环境在利用多源异构数据方面遇到的问题,进行了面向地理问题求解的数据表达模型(XGE-DRM)的研究。本文重点研究了多源、异构、跨领域地理数据的表达方式与组织规范,从原子数据层与对象组织层两个层次对XGE-DRM的基本原子构成与对象组成方式进行了阐述;通过对地理数据的结构与语义进行解析,显式表达地理数据的结构与语义;在结构清晰、语义明确的情况下,实现多源异构数据的抽取与交换,最终实现多源异构数据的共享。实验证明,文中提出的数据表达模型能够实现多源异构数据的通用表达,解决地理问题求解建模环境平台下数据共享的问题。

Extensible Geographic Environments （XGE） is a collaborative modeling environment which is designed for cooperative modeling by experts from different domains. In order to solve the problem of using multi-source heterogeneous data in XGE, a data representation model which named as XGE-DRM is proposed in this paper. Based on study of expression approach and organization criterion about multi-source, heterogeneous and multi-domain geo-data, XGE-DRM is divided into two levels, i. e. ： the atom representation level and the object representation level. Prototype, semantic, metadata, expression, spatial reference and unit about data expression are discussed in atom representation level, and the expressions about relationships among data are also mentioned. The expression of geo-Entity is studied in the object representation level considering atom expression. In this level, each Entity has different aspects; each aspect is with XML technology for reuse. Based on way, and can can be shared designed for different research domains, and can be saved as template XGE-DRM, data construction and semantic can be parsed by a uniform be explicitly expressed. Owning to legible expression for data construction and semantic, geo-data expediently by different actors in collaborative modeling environment such as data owner and model builders who expressing their data and converting data from different kinds of data which is heterogeneous. Lastly an experiment about groundwater mining was designed in this paper; it involves integration of time series model and groundwater model. The experiment has shown that this XGE-DRM can meet the requirement of commom expression and efficiently using of geo-data, and it can support the geographic problem-solving oriented modeling environments.