This National Science Foundation (NSF) Project Grant award, funded under the Computer and Information Science and Engineering program (CFDA 47.070), supports the development of an automated quality assurance and quality control (QAQC) system for observational geologic data. The $244,600 award to Texas A&M University aims to create two complementary algorithms, one using machine learning and one based on expert logic, to evaluate the quality and completeness of field- and lab-based geological data. The project also involves developing a user interface to allow geologists to assess existing datasets and improve their own data collection. This work will promote the use of shared, high-quality data across disciplines, enabling regional-scale modeling and expanding the incorporation of diverse datasets into analyses. No sub-awards are planned under this grant, which runs from September 1, 2023, to August 31, 2027.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $244.6k | 8/30/23 |