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Construction of an open knowledge framework for geoscientific models.

Authors :
Xu, Kai
Yue, Songshan
Chen, Qingbin
Wang, Jin
Zhang, Fengyuan
Wang, Yijie
Ma, Peilong
Wen, Yongning
Chen, Min
Lü, Guonian
Source :
Transactions in GIS. Apr2024, Vol. 28 Issue 2, p154-175. 22p.
Publication Year :
2024

Abstract

Geoscientific models have rapidly developed in recent decades as effective tools to understand the past, perceive the present, and predict the future. However, with the increasing number of models available, discovering suitable ones and applying them properly in problem‐solving situations has become more challenging. Existing materials describing geoscientific models (e.g., articles, manuals, handbooks, metadata documents, and web pages) are scattered and varied in structure and content. To help model users from different disciplinary backgrounds find, access, implement, and reuse models more conveniently, we propose an open knowledge framework for geoscientific models. The knowledge framework includes three levels: a resource level for indicating where to find a model, a connection level for indicating what materials are related to a model, and an application level for indicating how the model is applied. Through such a three‐level framework, model users can collaboratively provide descriptive information for a model, link different materials to a model (e.g., data, references, and tools), and contribute experiences regarding model application in practical cases (as reusable solutions). Thus, a web‐based community can be formed to facilitate the better use of geoscientific models. This article introduces the Open Geographic Modeling and Simulation System (OpenGMS) as the implementation of this open knowledge framework. Case studies are given to showcase the effectiveness and capability of the proposed framework. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13611682
Volume :
28
Issue :
2
Database :
Academic Search Index
Journal :
Transactions in GIS
Publication Type :
Academic Journal
Accession number :
176535719
Full Text :
https://doi.org/10.1111/tgis.13134