Automatic data matching for geospatial models: a new paradigm for geospatial data and models sharing

Abstract

ABSTRACTWith the development of global climate and environmental research, geospatial models are becoming more comprehensive and complex and, therefore require more and more input data. In order to improve the efficiency and to save time, labour and money during the preparation of input data, after a discussion of other related studies, this paper describes a new framework that matches existing open web data with geospatial models. The basic idea and general framework are introduced first; four key issues are then studied in detail. The advantages of the new framework are that it can automatically judge whether the open data is the consistent with the input data of the geospatial model according to data similarity values based on unified description factors; if they are not fully consistent, the differences can be intelligently handled using corresponding web processing services and finally, fully matched data can be obtained for use in the geospatial model. Thus, this framework may lead to the development of a new paradigm that links and promotes geospatial data and models sharing. This will not only lead to the greater application of geospatial models, but also greatly amplify the value and usability of open data.