Digitization TCN: Collaborative Research: oVert: Open Exploration of Vertebrate Diversity in 3D

数字化 TCN：合作研究：oVert：3D 脊椎动物多样性的开放探索

• 批准号: 1701714
• 负责人: David Blackburn
• 金额: $ 80.82万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701714&HistoricalAwards=false
• 关键词: Digitization; TCN; Collaborative; Research; oVert

The oVert (openVertebrate) Thematic Collection Network (TCN) will generate and serve high-resolution digital three-dimensional (3D) data for internal anatomy across vertebrate diversity. Via a network of digitization centers across the US, more than 20,000 fluid-preserved specimens representing over 80% of the living genera of vertebrates will be CT-scanned. This will provide broad coverage for exploration and research on all major groups of vertebrates. Contrast-enhanced scans will be generated that reveal soft tissues and organs. This collection of digital imagery and three-dimensional volumes will be open for exploration, download, and use to address questions related to the discovery of new species, documenting patterns of anatomical diversity and growth, and testing hypotheses of function and evolution. The resource will provide unprecedented global access to valuable specimens in US museum collections and will develop best practices and guidelines for high-throughput CT-scanning, including efficient workflows, preferred resolutions, and archival formats that optimize the variety of downstream applications. Museum specialists will be trained on the generation, curation, and distribution of 3D data, researchers in using 3D anatomical data, and high school and undergraduate students in the tools for creating 3D anatomical models. To drive the use of these digital specimens by K-12 STEM educators, teacher-driven workshops that generate freely available lesson plans focused on specific science standards that are based on digital and printed 3D models of specimens in US museum collections.Data generated by oVert will serve as a catalyst for diverse research projects focused on understanding the vertebrate morphological diversity and will dramatically increase the accessibility of specimens housed in US scientific collections. These anatomical phenotypes represent a common currency that facilitates integration across the fields of taxonomy, evolution, developmental biology, comparative physiology, functional anatomy, paleontology, and ecology. The x-ray computed tomography (CT) scanning gemerates high-resolution digital anatomical data, represented as both 2D image stacks and 3D volumes and surfaces. With these 3D digital specimens, US and international research communities will be able to (1) diagnose, describe, and infer patterns of relationships among both living and extinct vertebrates, (2) test hypotheses of morphological evolution such as patterns of disparity, modularity, and phenotype-environment correlations, (3) develop structure-function models for testing hypotheses about morphological adaptations related to, e.g., feeding and locomotion, and (4) explore relationships between brain and nervous system anatomy and both sensory and musculoskeletal function. The 3D data will be distributed globally through MorphoSource, an on-line data repository for 3D biological specimen data, which will capture standardized metadata, ingest legacy data from previous and existing projects, and will supply media information to data aggregators including iDigBio (www.idigbio.org). Training workshops, both on-site at participating institutions and national society meetings of scientists and educators are planned to foster innovation and capabilities for users of 3D image data.

公开(开放脊椎动物)主题收集网络(TCN)将为脊椎动物多样性的内部解剖生成并提供高分辨率的数字三维(3D)数据。通过美国各地的数字化中心网络，20,000多个液体保存的标本将接受CT扫描，这些标本代表了80%以上的脊椎动物活体物种。这将为所有主要脊椎动物群体的探索和研究提供广泛的覆盖范围。将生成显示软组织和器官的增强扫描。这些数字图像和三维卷将开放供探索、下载和使用，以解决与发现新物种有关的问题，记录解剖多样性和生长的模式，并测试功能和进化的假设。该资源将在全球范围内前所未有地获取美国博物馆藏品中的有价值的标本，并将制定高通量CT扫描的最佳实践和指导方针，包括高效的工作流程、首选的分辨率和优化下游应用的各种档案格式。博物馆专家将接受有关3D数据的生成、管理和分发的培训，研究人员将接受使用3D解剖数据的培训，高中生和本科生将接受创建3D解剖模型工具的培训。为了推动K-12 STEM教育工作者对这些数字标本的使用，教师主导的研讨会将生成免费提供的教案，这些教案侧重于特定的科学标准，这些标准基于美国博物馆收藏的标本的数字和打印3D模型。OPRORT产生的数据将成为专注于了解脊椎动物形态多样性的不同研究项目的催化剂，并将极大地增加美国科学藏品中标本的可及性。这些解剖表型代表了一种共同的货币，促进了分类学、进化论、发育生物学、比较生理学、功能解剖学、古生物学和生态学领域的整合。X射线计算机断层扫描(CT)产生高分辨率的数字解剖数据，表示为2D图像堆叠和3D体积和表面。有了这些3D数字标本，美国和国际研究团体将能够(1)诊断、描述和推断现存和灭绝脊椎动物之间的关系模式，(2)测试形态进化假说，如差异、模块化和表型与环境的相关性，(3)开发结构-功能模型，用于测试与摄食和运动相关的形态适应假说，以及(4)探索脑和神经系统解剖以及感觉和肌肉骨骼功能之间的关系。3D数据将通过MorPhoSource在全球范围内发布，这是一个3D生物标本数据的在线数据储存库，它将捕获标准化的元数据，从以前和现有的项目中摄取遗留数据，并将向包括iDigBio(www.idigBio.org)在内的数据聚合器提供媒体信息。计划在参与机构和国家学会科学家和教育工作者会议上举办培训讲习班，以促进3D图像数据用户的创新和能力。

项目成果

TopoAngler: Interactive Topology-Based Extraction of Fishes

• DOI: 10.1109/tvcg.2017.2743980
• 发表时间: 2018
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: A. Bock;Harish Doraiswamy;Adam P. Summers;Cláudio T. Silva

Carotid foramen size in the human skull tracks developmental changes in cerebral blood flow and brain metabolism

人类头骨中颈动脉孔的大小追踪脑血流量和脑代谢的发育变化

• DOI: 10.1002/ajpa.23809
• 发表时间: 2019
• 期刊: American Journal of Physical Anthropology
• 影响因子: 2.8
• 作者: Harrington, Arianna R.;Kuzawa, Christopher W.;Boyer, Doug M.
• 通讯作者: Boyer, Doug M.

Functional coupling in the evolution of suction feeding and gill ventilation of sculpins (Perciformes: Cottoidei)

• DOI: 10.1093/icb/icz022
• 发表时间: 2019-08-01
• 期刊: INTEGRATIVE AND COMPARATIVE BIOLOGY
• 影响因子: 2.6
• 作者: Farina, S. C.;Knope, M. L.;Bemis, W. E.
• 通讯作者: Bemis, W. E.

Killing them softly: Ontogeny of jaw mechanics and stiffness in mollusk‐feeding freshwater stingrays

轻柔地杀死它们：软体动物下颌力学和刚度的个体发育——喂养淡水黄貂鱼

• DOI: 10.1002/jmor.20984
• 发表时间: 2019
• 期刊: Journal of Morphology
• 影响因子: 1.5
• 作者: Rutledge, Kelsi M.;Summers, Adam P.;Kolmann, Matthew A.
• 通讯作者: Kolmann, Matthew A.

The Walking Dead: Status Report, Data Workflow and Best Practices of the oVert Thematic Collections Network

• DOI: 10.3897/biss.2.26078
• 发表时间: 2018-06
• 期刊: Biodiversity Information Science and Standards
• 作者: G. Watkins-Colwell