The Human Body Atlas: High-Resolution, Functional Mapping of Voxel, Vector, and Meta Datasets

人体图谱：体素、矢量和元数据集的高分辨率功能映射

• 批准号: 10397321
• 负责人: KATY BORNER
• 金额: $ 150万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-21 至 2022-06-20
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10397321
• 关键词: Anatomy; Artificial Intelligence; Atlases; Biology; Biometry; Cataloging; Cells; Collaborations; Communication; Data; Data Set; Ecosystem; Goals; Human; Human BioMolecular Atlas Program; Human body; Image; Individual; Infrastructure; Maps; Metadata; Methods; Modeling; Molecular; Organ; Resolution; Resources; Tissues; Visual; Visualization; Work; base; cell type; data exploration; data standards; design; human imaging; improved; interoperability; tool; vector

Project Summary/Abstract The ultimate goal of the HIVE MC-IU effort is to develop a common coordinate framework (CCF) for the healthy human body that supports the cataloguing, exploration, and download of differenttypes of tissue and individual cell data. The CCF will use different visual interfaces in order to exploit human and machine intelligence to improve data exploration and communication. The proposed effort combines decades of expertise in data and network visualization, scientific visualization, biology, and biomedical data standards. The goal is to develop a highly accurate and extensible multidimensional spatial basemap of the human body with associated data overlays. This basemap will be designed for online exploration as an atlas of tissue maps composed of diverse cell types, developed in close collaboration with the HIVE MC-NYGC team. 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 multiple levels (whole body, organ, tissue, cells). MC-IU will work in close collaboration with the HIVE Infrastructure and Engagement Component (IEC) and tools components (TCs) to connect and integrate further computational, analytical, visualization, and biometric resources driven by spatial context.

项目摘要/摘要 蜂巢MC-IU工作的最终目标是开发一个共同的协调框架 (CCF)，支持编目、探索和下载 不同类型的组织和单个细胞数据。CCF将使用不同的可视界面 为了利用人和机器的智能来改进数据探索和 沟通。拟议的工作结合了数十年在数据和网络方面的专业知识 可视化、科学可视化、生物学和生物医学数据标准。我们的目标是 开发高精度、可扩展的人体多维空间底图 具有相关联的数据覆盖。此底图将作为地图集设计用于在线探索 由不同细胞类型组成的组织图谱，与蜂巢密切合作开发 MC-NYGC团队。为了实现此功能，我们将开发映射和连接的方法 元数据、像素/体素数据和提取的矢量数据，允许用户在 多层次(全身、器官、组织、细胞)。MC-IU将与 配置单元基础架构和接洽组件(IEC)和工具组件(TC) 连接和集成进一步的计算、分析、可视化和生物识别资源 由空间背景驱动。

项目成果

Visualizing learner engagement, performance, and trajectories to evaluate and optimize online course design

• DOI: 10.1371/journal.pone.0215964
• 发表时间: 2019-05-06
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Ginda, Michael;Richey, Michael C.;Borner, Katy
• 通讯作者: Borner, Katy

The impact of air transport availability on research collaboration: A case study of four universities

• DOI: 10.1371/journal.pone.0238360
• 发表时间: 2018-11
• 期刊: PLoS ONE
• 影响因子: 3.7
• 作者: Adam Ploszaj;Xiaoran Yan;K. Börner

Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments

• DOI: 10.1073/pnas.1807180116
• 发表时间: 2019-02-05
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Boerner, Katy;Bueckle, Andreas;Ginda, Michael
• 通讯作者: Ginda, Michael