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Creating Scalable, Reliable, Sustainable Infrastructure for FAIR Data

Creating Scalable, Reliable, Sustainable Infrastructure for FAIR Data
为公平数据创建可扩展、可靠、可持续的基础设施
批准号:
10166440
负责人:
Yang Chai
金额:
$17.5万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-01 至 2021-07-31

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中文摘要
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英文摘要
PROJECT SUMMARY The goal of the FaceBase III Hub is to create a FAIR data repository to serve the entire community of dental and craniofacial researchers by sharing diverse data related to craniofacial development and dysmorphia. To meet this goal, FaceBase is built on Deriva, an open-source data management system designed with FAIR data principles in mind. This platform has allowed FaceBase to evolve with changing requirements for data on new experimental methodologies and instruments, additional model organisms, cell characterization, integration of computational pipelines, and visualization interfaces. Currently, we implement Deriva on private and public clouds using a “data center-in-the-cloud” format; i.e., treating the cloud like a traditional remote computer, to run virtual machine images and conventional data storage. However, cloud platforms such as Amazon Web Services offer a wide range of cloud-native services beyond virtual machines which if fully leveraged would drastically improve important aspects of Deriva that would directly benefit FaceBase. Hence, we propose to enhance Deriva for cloud-based operations to address three key aspects of Deriva in support of FaceBase and its other NIH communities: scalability, reliability, and sustainability. Specifically, we plan to use AWS native services to improve its scalability (Aim 1), decouple Deriva services to run in containerized execution environments to ensure its reliability (Aim 2), and develop cost management dashboards to monitor and predict costs of operating in the cloud to achieve sustainability (Aim 3). The AWS native services are fully managed and highly-scalable, and offload much of the overhead of system operations and maintenance. Improvements in Deriva scalability, reliability, and sustainability achieved by these Aims will allow the FaceBase Hub to provide the growing community of data contributors and users with better service. In addition, many other user communities such as GUDMAP, (Re)Building a Kidney, the Kidney Precision Medicine Project (NIDDK) and the Common Fund Data Environment (OD) rely on Deriva, and all of the improvements resulting from these Aims would yield a direct and immediate benefit to thousands of additional users.
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Center for TMD IMPACT
Hybrid- and Multi-Cloud Storage Strategies for Cost-effective Deployment of Data Resources
USC FaceBase III Craniofacial Development and Dysmorpholoy Data Management and Integration Hub
Mechanisms and rescue of craniosynostosis associated with gene-environment interaction
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