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-speci?c 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 work?ow-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.
To gain a better understanding of variation in organ function that in?uences health and disease, it is critical to have access to an atlas of molecular tissue organization. We will contribute to the Human BioMolecular Atlas Program (HuBMAP) by developing tools for visualization and exploration of HuBMAP data. The proposed tools will align with the FAIR principles and maximize the bene?t of data sets generated by the consortium for researchers and the public.
