Daniel Garijo
Deborah Khider
Rafael Ferreira da Silva
Craig Knoblock
Daniel Hardesty-Lewis
ABSTRACT
Understanding the interactions between natural processes and human activities poses major challenges as it requires the integration of models and data across disparate disciplines. It typically takes many months and even years to create valid end-to-end simulations as different models need to be configured in consistent ways and generate data that is usable by other models. MINT is a novel framework for model integration that captures extensive knowledge about models and data and aims to automatically compose them together. MINT guides a user to pose a well-formed modeling question, select and configure appropriate models, find and prepare appropriate datasets, compose data and models into end-to-end workflows, run the simulations, and visualize the results. MINT currently includes hydrology, agriculture, and socioeconomic models.
- S. D. Peckham, E. W. H. Hutton, and B. Norris, "A component-based approach to integrated modeling in the geosciences: The design of CSDMS," Comput. Geosci., vol. 53, pp. 3--12, 2013. Google Scholar
Digital Library
- Y. Gil et al., "MINT: Model Integration Through Knowledge-Powered Data and Process Composition," in Proceedings of the Ninth International Congress on Environmental Modeling and Software, 2018.Google Scholar
Index Terms
- An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models
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