Creating Scalable, Reliable, Sustainable Infrastructure for FAIR Data

项目摘要 FaceBase III Hub的目标是创建一个FAIR数据存储库， 牙科和颅面研究人员的社区，通过分享与颅面相关的各种数据， 发育和发育障碍。为了实现这一目标，FaceBase建立在开源的Deriva基础上， 数据管理系统的设计与公平的数据原则铭记。该平台具有 允许FaceBase随着新实验数据需求的变化而发展 方法和仪器，其他模式生物，细胞表征， 计算管道和可视化接口。 目前，我们使用“云中数据中心”在私有云和公共云上实施Deriva。 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。但是，Amazon Web Services等云平台提供了 除了虚拟机之外，还提供广泛的云原生服务，如果充分利用， 彻底改善Deriva的重要方面，这将直接使FaceBase受益。因此，我们认为， 我们建议增强Deriva的云操作能力，以解决以下三个关键问题： Deriva支持FaceBase及其其他NIH社区：可扩展性，可靠性和 持续发展具体来说，我们计划使用AWS原生服务来提高其可扩展性（目标1）， 将Deriva服务解耦以在容器化执行环境中运行，以确保其可靠性 (Aim 2），开发成本管理仪表板，以监控和预测运营成本， 云计算实现可持续性（目标3）。AWS原生服务完全托管， 高度可扩展，并减轻系统操作和维护的大部分开销。 通过这些目标实现的Deriva可扩展性、可靠性和可持续性的改进将 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，（重新）建立一个 肾脏，肾脏精准医学项目（NIDDK）和共同基金数据 环境（OD）依赖于Deriva，所有这些目标带来的改进都将 为成千上万的用户带来直接和直接的好处。

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.