Interoperability, the ability for independently produced data and models to work together with minimal effort, is a major challenge to modern open science. Automating the selection, coupling, and execution of data and models within complex scientific workflows is particularly challenging. In collaboration with the United Nations (U.N.) and Basque Centre for Climate Change, the USGS built a tool called ARIES for SEEA. The name stands for Artificial Intelligence for Environment & Sustainability (ARIES) for System of Environmental Economic Accounting (SEEA). ARIES for SEEA enables countries to more rapidly assemble natural capital accounts using the best-available data and models. The tool uses the AI techniques of semantics and machine reasoning. ARIES for SEEA improves the reusability of scientific data and models. It also increases equitable access to scientific knowledge, particularly in the Global South.  

U.S.-based applications of ARIES are also being explored. For example, a USGS Community for Data Integration project from 2022is working to improve the semantic interoperability  of hydrologic and ecological data and models in the Colorado River Basin. This interoperability will improve our understanding of the effects of long-term drought. 

• ARIES for SEEA Webpage: https://seea.un.org/content/aries-for-seea  

• FY22 CDI Project: https://www.usgs.gov/centers/community-for-data-integration-cdi/science/building-usgs-community-fair-integrated-modeling