HuBMAP HIVE Tools Component

项目总结 我们建议贡献一套基于云的数据可视化、探索和分析工具，这将使 HuBMAP数据公平，并将使这一宝贵资源在社区内得到广泛重用。我们设想要 支持面向高级用户的批处理和交互分析工具，以及基于任务的fic用户界面分析工具 适用于对计算方法没有深入了解的最终用户。我们的目标也是为用户提供 能够通过可视化界面与分析来源进行交互。这些将以方法为基础 这是我们为与Workfl交互而开发的数据来源，用于可重现的生物医学研究。 我们的可视化工具将是交互式的，设计用于数据探索和交流。基于 我们的Vistory方法用于可重现的可视分析，我们将在这两个不同的任务之间创建一座桥梁。 这也将使与远程合作者共享观察和发现成为可能。分析和 可视化工具将嵌入到框架中，使我们能够整合和部署由创建的工具 蜂巢、HuBMAP和更广泛社区的成员。只要有可能，我们将改进现有的工具 并将它们包装到一个基于容器、可扩展且与云无关的部署框架中。要启用搜索和 为了探索HuBMAP将生成的巨大数据空间，我们建议实现一组 支持系统导航和检索组学和成像数据的工具，超越了基于文本的搜索。我们会 重点是使用元数据和本体来通过类似于我们的Satori系统的接口来实现这一点 用于本体论指导的生物医学数据存储库的可视化探索。最后，我们将支持协作 通过可视化分析工具在HuBMAP和HIVE内实现对整个项目进度的监控 以及数据质量，包括计划实验的时间表、提交的数据等。

PROJECT SUMMARY We propose to contribute a suite of cloud-based data visualization, exploration, and analysis tools that will make HuBMAP data FAIR and will enable broad re-use of this valuable resource within the community. We envision to support both batch and interactive analysis tools for power users, as well as task-specific UI-based analysis tools for end users without deep knowledge of computational approaches. Our goal is to also provide users with the ability to interact with analysis provenance in through visual interfaces. These will be based on the approaches that we developed for interaction with workflow-derived data provenance for reproducible biomedical research. Our visualization tools will be interactive and designed for both data exploration and communication. Based on our Vistories approach for reproducible visual analysis, we will create a bridge between these two distinct tasks. This will also make it possible to share observations and discoveries with remote collaborators. Both analysis and visualization tools will be embedded in a framework that will enable us to incorporate and deploy tools created by members of the HIVE, HuBMAP, and the broader community. Whenever possible, we will enhance existing tools and wrap them into a container-based, scalable, and cloud-agnostic deployment framework. To enable search and exploration of the enormous data space that will be generated by HuBMAP, we propose to implement a set of tools that enable systematic navigation and retrieval of omics and imaging data beyond text-based search. We will focus on the use of metadata and ontologies to accomplish this through interfaces similar to our SATORI system for ontology-guided visual exploration of biomedical data repositories. Finally, we will support collaboration within HuBMAP and the HIVE through visual analysis tools that enable monitoring of the overall project progress and data quality, including timelines for planned experiments, submitted data, and others.