Developing a data model for understanding geographical analysis models with consideration of their evolution and application processes
Journal:《Transactions in GIS》, November 2018
Cite as:Chen M, Yang C, Hou T, Lü G, Wen Y, Yue S. 2018. Developing a data model for understanding geographical analysis models with consideration of their evolution and application processes. Transactions in GIS, Doi：https://doi.org/10.1111/tgis.12484
Abstract:Geographical analysis models are widely employed to mirror real phenomena and processes on Earth. The current geo‐graphical analysis models can provide prediction and deci‐sion support‐oriented information in various domains through analysis and simulation results. However, the com‐plexity of models is increasing due to their continuous devel‐opment and related research, and the relationships bet ween models are becoming increasingly complicated, which se‐verely hinders the ability to select and use suitable models. To bridge the requirements of model understanding with related abundant information, a data model for geographical analysis models is designed with consideration of their evo‐lution and application processes. In addition to basic meta‐data (e.g., name, classification, and modeling approach), evolution and application information, which is often ne‐glected in traditional model expression methods, can pro‐vide clues about model development histories and usage relationships. Thus, this information will provide scientists with a comprehensive understanding and will form an over‐all picture of geographic models that can be used for future research. Based on the analysis of the elements related to the evolution and application information, the data model is designed and an information abstraction strategy is pro‐posed. The Soil and Water Assessment Tool (SWAT) is em‐ployed as a case study to show the capacity of the designed data model to contribute to both sharing of geographical analysis model knowledge and further model analysis.