Integrated, collaborative modeling is increasingly recognized as key long-term goal for USGS and other science practitioners. It is also a key purpose and outcome of the FAIR data principles. Yet abundant challenges exist to making data and scientific models available and interoperable, including (1) semantics, (2) data storage and services, (3) the use of multiple programming languages and modeling paradigms (both deductive and inductive approaches, including machine learning), (4) uncertainty propagation, and (5) ensuring data and model reuse at appropriate spatiotemporal scales. Modeling protocols and frameworks, like those of the Community Surface Dynamics Modeling System (CSDMS) and Artificial Intelligence for Ecosystem Services (ARIES)/Integrated Modelling Partnership, provide examples of practical methods to overcome these integration challenges. In this session, presenters will address theories and methods to overcome the aforementioned challenges, potential applications, along with potential lessons learned that could inform integrated modeling for USGS and beyond.
Science support framework category: Applications
Notes Document: https://tinyurl.com/CDI0605-Bagstad