基于4FS的状态——事件时空数据模型

A 4FS-based State-event Spatial-temporal Data Model

由于时空数据呈指数产生,研究问题具有多样性和不确定性,在地学时空数据的存储、表达和分析研究基础上提出面向地学的4FS的状态——事件时空数据模型。模型采用面向对象与面向过程相结合的方式,以面向对象表达时空数据,以面向过程表达时空变化关系。空间数据由几何特征、空间关系、专题属性、驱动事件四特征(4F)表达。时空数据对象由四特征序列(4FS:几何特征序列、空间关系序列、专题属性序列、驱动事件序列)表达。时空变化关系则通过改进状态——事件模型,增强事件语义,以面向过程结构表达。通过对时空数据表达、时空变化表达、时空对象检索进行论述与实现,突出表达此时空数据模型在完整表达时空语义、因果关系和数据检索效率等方面的优点。

Because of the exponential generation of spatial-temporal data and variable diversity and uncer- tainty of study problems, it was put forward an oriented geoscience universal spatial temporal data model based on the storage, expression and analysis of geoscience spatial temporal data by analyzing the advanta- ges and disadvantages of the current spatial temporal data model. This model is based on the combination of object oriented and process oriented. The spatial-temporal data is expressed by object-oriented and the relationship of temporal and spatial variation is expressed by express-oriented. Spatial data is expressed by four features （4F） including the geometric features, the spatial relationships, the thematic attributes, the driven events. Spatial temporal data object is expressed by four features series （4FS. the geometric feature series, the spatial relation series, the thematic attribute series and the driven event series）. The relation- ship of temporal and spatial variation enhances events semantics and expressed by process-oriented by im- proving state-event model. By expressing spatial-temporal data and temporal and spatial variation and dis- cussing and realizing of spatial-temporal object retrieval, the paper highlights the advantages of the spatial- temporal data model in expressing spatial-temporal semantics completely, causal relationship and the re- trieval efficiency of data.