Description

In this video podcast, Allissa Dillman and Andreas Bueckle discuss and demonstrate the Human Reference Atlas (HRA) Organ Gallery, a virtual reality (VR) application that lets users explore the HRA in immersive 3D. Andreas also presents the “HRA Powers of Ten,” a data integration module in development that uses the HRA Common Coordinate Framework (CCF) to harmonize, visualize, and explore data from the small/large intestine, lymph node, skin, and liver. The HRA Organ Gallery is available, for free, to anyone at https://www.meta.com/experiences/5696814507101529. A paper describing the concept of the HRA Organ Gallery is available at https://doi.org/10.3389/fbinf.2023.1162723.

Single-cell atlassing portals such as the Human BioMolecular Atlas Project (HuBMAP), the Cellular Senescence Network (SenNet), and the Human Tumor Atlas Network (HTAN) publish datasets across scales for multiple organs of the adult human body in health, aging, and disease. This data can be interrogated semantically and spatially, usually on 2D screens with limited 3D affordances. Imagine, for example, examining the 3D location of a cell in the context of a tissue or zooming across multiple orders of magnitude. To be tackled effectively, 3D problems require 3D platforms.

Guest Bio

Andreas Bueckle, Ph.D. (https://andreas-bueckle.com), is the Research Lead in the Cyberinfrastructure for Network Science Center at the Luddy School of Informatics, Computing, and Engineering (SICE) at Indiana University in Bloomington, IN. His research interest is interactive information visualization in XR. Andreas has a TEDx talk titled “Living and Learning in the Metaverse” (available on YouTube and on the TED website). From 2023-2025, he was awarded two JumpStart Fellowships by the National Institutes of Health (NIH) to advance multiscale exploration of the human body in VR with the Human Reference Atlas Organ Gallery. In 2025, he received an R03 award, also by the NIH, to advance the integration of 3D reference organs with data visualizations of cell type populations for Common Fund datasets in 3D and VR.