Flexible Hybrid Cloud Infrastructure for Seamless Integration and Use of Human Biomolecular Data and Reference Maps [1 of 5]

人类生物分子图谱计划(HuBMAP)正在重新定义我们对人类的理解 通过恢复多尺度的组织结构--解剖学、组织学和分子--在 史无前例的分辨率，通过计算集成各种实验 测量。HuBMAP集成、可视化和接洽(HIVE)合作实验室 跨学科组件之间的努力，开发用于数据摄取和 处理，使跨越数十个生物分子分析的数据集能够在 HuBMAP门户，领导开发人类共同坐标框架(CCF)， 构建人类组织的分子和空间分辨参考图，开发 绘制解释新数据集的框架图，并协调广泛的 在HuBMAP内部和与更广泛的社区开展协作活动。在制作中 在HuBMAP阶段，蜂巢将构建人类参考地图集(HRA)，建立 HuBMAP门户网站是人体组织参考图和多模式单细胞数据的首选资源。蜂窝的下一次迭代将围绕一个关节合并HuBMAP联盟 愿景，开发尖端和可扩展的工具来实现这一愿景，并确保其公开传播 面向更广泛的国际社会的合作伙伴和用户。 作为蜂窝基础设施组件(IC)，匹兹堡超级计算中心(PSC)、 匹兹堡大学(匹兹堡)和斯坦福大学将提供基础设施，基于我们 灵活的混合云微服务架构，以及社区参与，将 在生产阶段支持这一愿景的交付。为实现这一目标，我们将集中力量 在以下关键领域：1)固化和接收：提高数据接收的自动化程度 HuBMAP数据提供商、社区合作伙伴和一般研究社区，以最大限度地 建立人力资源评估的效率和有用性；2)集成：自动集成和绘图 根据数据标准将摄取的数据提交给HRA；3)可查找性和可访问性： 后端资源在API和容器、服务、 和文档，最大限度地减少集成搜索、查询 在多个空间尺度和多个层之间分析/对齐和查看组织图 4)互操作：HuBMAP知识图的扩展以进行翻译 HuBMAP数据、HRA资产和社区数据通过本体相互关联；5)分析： 基础架构支持，最大限度地为用户提供可扩展的分析和工作流 HuBMAP和用户贡献的数据和工具，包括针对 人力资源管理局；和6)可持续性：维护开放的工具、数据和基础设施，以便在更远的地方重复使用 生产阶段。我们将发展和强化我们的协作、协调和 由IC领导，所有蜂巢成员和参与者都有相当大的领导力 来自所有HuBMAP成员。

The Human BioMolecular Atlas Program (HuBMAP) is redefining our understanding of the human body by recovering multi-scale tissue organization -- anatomical, histological, and molecular -- at unprecedented resolution, through computational integration of diverse experimental measurements. The HuBMAP Integration, Visualization & Engagement (HIVE) Collaboratory is an effort among interdisciplinary components developing pipelines for data ingestion and processing, enabling visualization of datasets spanning dozens of biomolecular assays on the HuBMAP portal, leading the development of a human common coordinate framework (CCF), constructing molecularly and spatially resolved reference maps of human tissues, developing mapping frameworks for the interpretation of new datasets, and coordinating extensive collaborative activities both within HuBMAP and with the broader community. In the production phase of HuBMAP, the HIVE will construct a Human Reference Atlas (HRA), establishing the HuBMAP Portal as the “go-to” resource for human tissue reference maps and multimodal singlecell data. The next iteration of the HIVE will coalesce the HuBMAP Consortium around a joint vision, develop cutting-edge and scalable tools to achieve it, and ensure its open dissemination to partners and users across the wider international community. As the HIVE Infrastructure Component (IC), the Pittsburgh Supercomputing Center (PSC), the University of Pittsburgh (Pitt), and Stanford University will provide infrastructure, based on our flexible hybrid cloud microservices architecture, along with community engagement, that will support delivery of this vision in the production phase. To accomplish this, we will focus our efforts in the following key areas: 1) Curation and Ingestion: Increased automation of data ingestion from HuBMAP data providers, community partners, and the general research community to maximize efficiency and usefulness for building the HRA; 2) Integration: Automated integration and mapping of ingested data to the HRA based on data standards; 3) Findability and Accessibility: Manifestation of backend resources in the modular architecture of APIs and containers, services, and documentation that minimize user friction in integrated searching, querying, analyzing/aligning and viewing of tissue maps at multiple spatial scales and among multiple layers of information; 4) Interoperability: Extension of the HuBMAP Knowledge Graph to translate HuBMAP data, HRA assets, and community data among one another via ontologies; 5) Analysis: Infrastructure support to maximally enable users with scalable analyses and workflows among both HuBMAP and user-contributed data and tools, including integration and mapping against the HRA; and 6) Sustainability: Sustainment of open tools, data, and infrastructure for reuse beyond the production phase. We will grow and harden our model for collaboration, coordination, and engagement led by the IC, with substantial leadership from all HIVE members and participation from all HuBMAP Members.