AI-Based Upgrades to Observational Data Centers to Facilitate Data Interoperability
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Argonne National Lab. (ANL), Argonne, IL (United States)
Focal Areas: (1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Focal areas 2 and 3 have critical dependencies to the modernization described. Key benefits to the focal areas: (1) Modernized observatory framework capable of agile adaptive observation, (2) Advanced instrument and data tagging supporting AI data acquisition for assimilation or validation, and (3) Widespread data interoperability bridging Earth system prediction scales
- Research Organization:
- Artificial Intelligence for Earth System Predictability (AI4ESP) Collaboration (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI ID:
- 1769667
- Report Number(s):
- AI4ESP--1107
- Country of Publication:
- United States
- Language:
- English
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