Abstract

Major societal and environmental challenges require forecasting how natural processes and human activities affect one another. Model integration across natural and social science disciplines to study these problems requires resolving semantic, spatio-temporal, and execution mismatches, which are largely done by hand today and may take more than two years of human effort. We are developing the Model INTegration (MINT) framework that incorporates extensive knowledge about models and data, with several innovative components: 1) New principle-based ontology generation tools for modeling variables, used to describe models and data; 2) A novel workflow system that selects relevant models from a curated registry and uses abductive reasoning to hypothesize new models and data transformation steps; 3) A new data discovery and integration framework that finds and categorizes new sources of data …

Date

January 1, 1970

Authors

Daniel Garijo, Yolanda Gil, Kelly M Cobourn, Ewa Deelman, Christopher Duffy, R Ferreira da Silva, Armen Kemanian, Craig Knoblock, Vipin Kumar, Scott Dale Peckham, Yao-Yi Chiang, Deborah Khider, Ankush Khandelwal, Jay Pujara, Varun Ratnakar, Maria Stoica, Binh Vu, Minh Pham

Journal

AGU Fall Meeting Abstracts

Volume

2018

Pages

IN31A-02