Như vậy đến nay, ĐÃ GIScience năm thiếu mô hình dữ liệu thích hợp để đại diện cho các quá trình, quá trình này như xói mòn, di cư và ô nhiễm phát tán. Nhu cầu mở rộng quan đại diện địa lý cho quá trình đã-được công nhận trong GIScience văn học (Pauquet năm 2001; Raper, 2000; Worboys, 2001) và báo nhận như một mục tiêu quan trọng trong Hiệp hội Đại học chương trình nghiên cứu GIS của (UCGIS) (McMaster và Usery năm 2005 ) | Chapter 5 nen A Process-oriented Data Model Femke Reitsma1 and Jochen Albrecht2 institute of Geography School of Geosciences The University of Edinburgh Scotland department of Geography Hunter College City University of New York USA Introduction Thus far GIScience has lacked an appropriate data model to represent processes processes such as erosion migration and pollution dispersal. The need for extending geographic representations for processes has been recognised in GIScience literature Peuquet 2001 Raper 2000 Worboys 2001 and acknowledged as a key goal in the University Consortium of GIS s UCGIS research agenda McMaster and Usery 2005 . Yuan et al. 2005 p. 132 posit that As the conceptual core of a geographic information system geographic representations determine what information is available for communication exploration and analysis. Hence research in extensions to geographic representations is critical to advancing geographic information science . In order to investigate change in space and time the theme of this book we need to be able to explicitly represent change as it occurs. Existing theories and data models for simulating processes focus on representing the state of the represented system at a moment in time. The future pattern of global temperature from a global climate change model or the distribution of humans in an agent-based simulation of disease spread for example only provides information about the status of the attributes of the system at each step of the simulation attributes such as temperature or agent health at a particular location. Information about the processes defined in the model is typically not expressed or represented in any form. In utilising a process-oriented data model we gain the advantage of being able to query analyse and visualise processes. This chapter presents a new process-oriented data model called nen which can be used to represent process information. The application of the nen data model to process modelling .
