The ultimate goal of the HIVE Mapping effort is to develop a common coordinate framework (CCF) for the healthy human body that supports the cataloguing of different types of individual cells, understanding the func- tion and relationships between those cell types, and modeling their individual and collective function. In order to exploit human and machine intelligence, different visual interfaces will be implemented that use the CCF in support of data exploration and communication. The proposed effort combines decades of expertise in data and network visualization, scientific visualization, mathematical biology, and biomedical data standards to develop a highly accurate and extensible multidimen- sional spatial basemap of the human body and associated data overlays that can be interactively explored online as an atlas of tissue maps. To implement this functionality, we will develop methods to map and connect metadata, pixel/voxel data, and extracted vector data, allowing users to ?navigate? across the human body along multiple functional contexts (e.g., systems physiology, vascular, or endocrine systems), and connect and integrate further computational, analytical, visualization, and biometric resources as driven by the context or ?position? on the map. The CCF and the interactive data visualizations will be multi-level and multi-scale sup- porting the exploration and communication of tissue and publication data--from single cell to whole body. In the first year, the proposed Mapping Component will run user needs analyses, compile an initial CCF using pre-existing classifications and ontologies; implement two interactive data visualizations; and evaluate the usa- bility and effectiveness of the CCF and associated visualizations in formal user studies.
This project will create a high-resolution, functional mapping of voxel, vector, and meta datasets in support of integration, interoperability, and visualization of biomedical HuBMAP data and models. We will create an ex- tensible common coordinate framework (CCF) to facilitate the integration of diverse image-based data at spa- tial scales ranging from the molecular to the anatomical. This project will work in close coordination with the HuBMAP consortium to help drive an ecosystem of useful resources for understanding and leveraging high- resolution human image data and to compile a human body atlas.