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CC* Data Storage: Remote Instrumentation Science Environment for Intelligent Image Analytics

CC* Data Storage: Remote Instrumentation Science Environment for Intelligent Image Analytics
CC* 数据存储:用于智能图像分析的远程仪器科学环境
批准号:
2322063
负责人:
Prasad Calyam
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2025-07-31

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中文摘要
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英文摘要
This NSF CC* project acquires and manages an on-premises data storage system supporting multiple scientific application storage needs for material science, biomedical science and other research activities on campus. The platform also provides an experimental testbed for developing innovations in intelligent image analytics. Project activities serve scientific experiments on university campuses that frequently involve control of specialized instruments such as scanning electron microscopes, and image data collection from those instruments. The significance of the project activities is in the automated handling of remote instrumentation and image analytics to overcome the manual processes in current practice that requires notable effort and time, and could lead to inconsistencies or errors. As a next-generation storage environment, the Remote Instrumentation Science Environment (RISE) developed in this project is a shared resource at the intra-campus level located at the campus datacenter and at the inter-campus level via a federated data sharing fabric. RISE ensures adherence to FAIR (findable, accessible, interoperable, and reusable) principles and equitable access. The RISE data storage system configurations are driven by scientific use cases of image analytics pipelines in areas such as material biomedical science, plant science, and biochemistry. The RISE storage system development features flexible web services to perform automated image data collection/analysis guided by an intelligent agent and involves collaborations with campus information technology group and the Open Science Grid. Usability studies in this project advance knowledge in terms of understanding challenges in orchestration and maintenance of large on-premise storage systems for diverse image analytics applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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