Mid-scale RI-1 (M1:IP): EduceLab: Infrastructure for Next-Generation Heritage Science

中型 RI-1 (M1:IP)：EduceLab：下一代遗产科学基础设施

基本信息

批准号：
2131940
负责人：
William Seales
金额：
$ 1400万
依托单位：
University of Kentucky Research Foundation
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2026-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2131940&HistoricalAwards=false
关键词：
Mid scale RI M1 IP

项目摘要

This project will create EduceLab, a data-centric instrument platform for Heritage Science (HS). HS applies the tools, techniques, and rigor of scientific measurement and inquiry to diverse heritage contexts, such as artifacts and curated collections, biological remains, and human-impacted environments. The proposed mid-scale instrument ecosystem is designed around key scientific capabilities that the research community has embraced as crucial and fundamental to addressing the challenging variability of HS contexts. The ecosystem includes materials characterization; advanced multimodal imaging (tomography, photography, photogrammetry); cyberinfrastructure and methodologies for capturing, structuring, and processing large-scale data sets; and mobile and flexibly-deployed instrumentation for in-situ data acquisition and initial evaluations. Viewed as a holistic ecosystem uniquely capable of addressing previously insoluble research questions in HS, EduceLab will be commissioned as operational clusters based on usage patterns that match the diverse HS communities and constituencies: laboratory equipment in a fixed, controlled environment for precise measurement and analysis (BENCH); mobile equipment that can be deployed on-site for collections and landscapes that cannot travel (MOBILE); and a protean environment for envisioning, building, and testing custom instrument configurations that address contexts impervious to laboratory analysis and on-site capabilities (FLEX). The clusters will be interconnected via cyberinfrastructure (CYBER) that powers efficient data flow through the entire infrastructure, from data acquisition to structured analysis, supporting the application of new techniques in data science and artificial intelligence. EduceLab will function as a novel Mid-scale Research Infrastructure – a variable scientific lens – for the rigorous, data-driven exploration of compelling heritage science research questions, engendering new discoveries as well as fundamental scientific advancement. Headquartered within the University of Kentucky’s William S. Webb Museum for Anthropology, EduceLab will build cohesion across a diverse group of national and international stakeholders and constituents: trainees/students; researchers in HS and in areas where data acquisition activities overlap; practitioners at institutions with active heritage collections and connected research efforts; and community members with investments in the ongoing conservation, preservation, study, dissemination, and educational activities.EduceLab in its organization will allow rigorous scientific exploration in the face of the unique challenges posed by natural and cultural heritage contexts. The EduceLab ecosystem will answer ongoing demands for agility and innovation in measurement, computational, and instrumentation solutions to these problems. Such advances will in turn continuously promote knowledge, growth, and innovation across a range of scientific disciplines involved in HS, including data science, computer science, computer vision, imaging science, systems engineering, chemical and materials engineering, anthropology, and cyberinfrastructure. The proposed instrumentation strongly aligns with the National Science Foundation’s “Big Ideas” initiatives, including: Growing Convergence Research (EduceLab and HS is a convergence activity in itself, blending a number of scientific disciplines and relying on robust collaborations for success); Harnessing the Data Revolution (EduceLab activities will be data-driven and data-intensive, relying on emerging computational tools at play across disciplines like chemistry, physics, and computer science to capture the essence of objects and their environments); and NSF INCLUDES (the EduceLab ecosystem combines STEM with heritage fields in a culturally informed way to strategically grow the interest and participation of underrepresented groups in STEM fields and increase societal public literacy and engagement with science and technology.).This project is jointly funded by Mid-Scale Research Infrastructure-Track 1 program, Information and Intelligent Systems, the Established Program to Stimulate Competitive Research (EPSCoR), and the Office of Advanced Cyberinfrastructure.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将创建一个以数据为中心的遗产科学仪器平台（HS）。 HS将科学测量和询问的工具，技术和严格应用于不同的遗产环境，例如人工制品和策划的收藏，生物遗骸以及人类影响的环境。拟议的中期仪器生态系统旨在围绕关键的科学能力设计，研究界对解决HS环境的挑战变异性至关重要。生态系统包括材料表征；先进的多模式成像（层析成像，摄影，摄影）；网络基础结构以及用于捕获，结构和处理大规模数据集的方法；以及可移动和灵活的仪器，用于原位数据获取和初步评估。被视为一个全面的生态系统，能够独特地解决HS中以前无法解决的研究问题，教育行将根据使用模式来委托使用与潜水员HS社区和宪法相匹配的使用模式：在固定的，受控的环境中进行精确测量和分析的实验室设备（BEN）；可以在现场部署的移动设备，用于无法旅行的收藏和景观；以及针对环境，构建和测试自定义仪器配置的蛋白质环境，这些仪器构造无法涉及实验室分析和现场功能（FLEX）的环境。群集将通过网络基础结构（网络）互连，从而为整个基础架构的有效数据流提供了从数据采集到结构化分析，支持新技术在数据科学和人工智能中的应用。 Educelab将充当一种新型的中尺度研究基础设施（一种可变的科学视角），用于严格，数据驱动的遗产科学研究问题，引起新发现以及基本的科学进步。 Educelab总部位于肯塔基大学威廉·S·韦伯人类学博物馆的人类学博物馆，将在国家和国际利益相关者和构成的潜水员群体上建立凝聚力：受训者/学生； HS和数据获取活动重叠的领域的研究人员；机构的从业人员进行了积极的遗产收集和互联研究工作；和社区成员在正在进行的保护，准备，研究，传播和教育活动上进行投资。在其组织中的Educelab将在面对自然和文化遗产环境所带来的独特挑战中进行严格的科学探索。此类进步将反过来跨越涉及HS的科学学科的知识，成长和创新，包括数据科学，计算机科学，计算机视觉，成像科学，系统工程，化学和材料工程，人类学和Cyberinfradstructure。 The proposed instrumentation strongly aligns with the National Science Foundation’s “Big Ideas” initiatives, including: Growing Convergence Research (EduceLab and HS is a convergence activity in itself, blending a number of scientific disciplines and relying on robust collaborations for success; Harnessing the Data Revolution (EduceLab activities will be data-driven and data-intensive, relying on emerging computational tools at play across disciplines like chemistry, physics, and computer science to捕获物体的本质及其环境）； NSF包括（教育行业生态系统将茎与遗产领域结合在一起，以一种文化知情的方式，以策略性地增强史蒂姆（STEM）群体的兴趣和参与，并参与STEM领域中的代表性不足，并增加社会公共素养和与科学和技术的融资。刺激竞争性研究（EPSCOR）和高级网络基础设施办公室。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估。