Creating Scalable, Reliable, Sustainable Infrastructure for FAIR Data

项目总结 FaceBase III Hub的目标是创建一个公平的数据存储库，以服务于 通过共享与颅面相关的不同数据，形成牙科和颅面研究人员社区 发育和变形障碍。为了实现这一目标，FaceBase建立在开源软件Deriva之上 数据管理系统的设计考虑到了公平数据原则。这个平台有 允许FaceBase随着新实验数据需求的变化而发展 方法和工具，其他模式生物，细胞特性，整合 计算管道和可视化界面。 目前，我们在私有云和公共云上实施了Derva，使用的是“云中数据中心” 格式；即，将云视为传统的远程计算机，以运行虚拟机映像 和常规数据存储。然而，亚马逊网络服务等云平台提供了 除虚拟机之外的多种本地云服务，如果充分利用这些服务将 极大地改进了派生的重要方面，这将直接使FaceBase受益。因此， 我们建议增强基于云的操作的派生，以解决以下三个关键方面 支持FaceBase及其其他NIH社区的Deriva：可伸缩性、可靠性和 可持续发展。具体地说，我们计划使用AWS原生服务来提高其可扩展性(目标1)， 分离派生服务以在容器化执行环境中运行，以确保其可靠性 (目标2)，并开发成本管理仪表板以监测和预测#年的运营成本 实现可持续发展的云(目标3)。AWS原生服务完全托管，并且 高度可扩展，可大大减轻系统运营和维护的开销。 通过这些目标实现的派生可伸缩性、可靠性和可持续性方面的改进将 允许FaceBase Hub为不断增长的数据贡献者和用户社区提供 更好的服务。此外，许多其他用户社区，如GUDMAP，(Re)Building a 肾脏、肾脏精准医学项目(NIDDK)和共同基金数据 环境(OD)依赖于派生，而由这些目标产生的所有改进将 为成千上万的额外用户带来直接和立竿见影的好处。

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.