International Geologiical Congress - Oslo 2008

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IEI-06 Data models and architectures

 

Ontological geosciences: An example of a layered Earth concept data model

 

Xiaoning Guo, China University of Geosciences (CUG) (China)
Kangping Sun, China University of Geosciences (China)
Qiuju He, China University of Geosciences (China)
Longjian Xie, China University of Geosciences (China)
 

 

By ontological geosciences we mean geosciences that are recognizable by computers and expressed in hierarchical concrete concepts and geoscientific concept models.

A layered Earth model is a basic model of the Earth system. The real Earth is more complex than the model. It is heterogeneous and arcs, rifts, shields, platforms and orogens might have different layered structures. The material of a layered earth may be divided into different lithofacies zones. There may be transitional boundaries and plumes within layered structures. It might seem impossible to represent the real Earth system in one model.

A geoscientific concept model is a system model that relates different geoscientific concepts and/or concept models. There are many possible relationships among geoscientific concepts and concept models. One important relationship that expresses the complex Earth system is a parent-child relationship that can refine the general concept or concept model into a more specific one. When a concept has been refined it is represented by its instances and/or data in the databases. Therefore, geoscientific data should be incorporated into the earth system model.

This paper introduces a layered Earth concept data model that we are constructing. It starts from SWEETĄŻs earth realm which defines several boundaries, layers and primary materials but adds more properties. Layers are divided into smaller ones and particular layered models are built for specific areas for which related data are collected. The emphases are on the topological relations between the layers and the relationships between models.

The layered Earth concept model is used in a multi-dimensional visual concept space for data mining.

 

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