Collaborative Research: Disciplinary Improvements: Creating a FAIROS Materials Research Coordination Network (MaRCN) in the Materials Research Data Alliance

协作研究：学科改进：在材料研究数据联盟中创建 FAIROS 材料研究协调网络 (MaRCN)

• 批准号: 2226414
• 负责人: David Elbert
• 金额: $ 44万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2226414&HistoricalAwards=false
• 关键词: Collaborative; Research; Disciplinary; Improvements; Creating; Collaborative; Research; Disciplinary; Improvements; Creating

The MaRCN (Materials research coordination network) will advance and coordinate FAIR data and support Open Science materials research nationally and internationally, bridging the fundamental gap between materials data and data-intensive methods including artificial intelligence and machine learning. The project will build on a range of planning and preparatory activities including the MGI (U.S. Materials Genome Initiative) and MaRDA (Materials Research Data Alliance), a community-based network spanning stakeholders in academia, industry, and publishing. By building on these initiatives to propose ways of advancing materials science to allow data to be leveraged in new ways, the MaRCN will enable the acceleration of materials design and deployment. This project will address multiple national research goals by advancing critical applications in renewable energy and sustainability, health, agriculture, energy storage, quantum computing, and advanced manufacturing.MaRCN will organize its activities around four over-arching themes: Data, Models, Training, and Impact. Activities undertaken as part of the Data theme include connecting and mediating the needs of data producers, data users, repository users, and publishers to make data deposition and access in trusted repositories the norm. The Models Theme will advance efforts and build community with a particular focus on the domains of electron microscopy and X-ray science. Training Theme activities will encompass a large number of convenings, including focus groups and workshops to seed and grow the network of educators and practitioners fluent in FAIR principles. The Impacts Theme will integrate and maximize the beneficial outcomes of the other themes and actively seek to harmonize the project’s activities with a large number of intersecting organizations with which the project is connected.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Directorate for Mathematical and Physical Sciences.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.

MARCN（材料研究协调网络）将促进和协调公平的数据，并在国际和国际上进行开放科学材料研究，从而弥合材料数据和数据密集型方法之间的基本差距，包括人工智能和机器学习。该项目将建立在一系列计划和准备活动的基础上，包括MGI（美国材料基因组计划）和Marda（材料研究数据联盟），这是一个基于社区的网络，涵盖了学术界，行业和出版的利益相关者。通过建立这些计划，提出了推进材料科学以允许以新方式利用数据的方法，MARCN将实现材料设计和部署的加速。该项目将通过推进可再生能源和可持续性，健康，农业，能源存储，量子计算和先进的制造业的关键应用来解决多个国家研究目标。MARCN将在四个主体主题中组织其活动：数据，模型，培训和影响。作为数据主题的一部分进行的活动包括连接和调解数据生产者，数据用户，存储库用户和发布者的需求，以使可信赖存储库中的数据沉积和访问规范。模型主题将促进努力并建立社区，特别关注电子显微镜和X射线科学领域。培训主题活动将包括大量召集，包括焦点小组和讲习班，以播种和发展教育工作者和从业者的网络，以公正的原则为基础。影响主题将整合并最大化其他主题的有益结果，并积极寻求将项目的活动与已连接该项目连接的大量相互联系的组织协调。这是由高级Cyber​​infrasture办公室颁发的奖项，共同支持了该委员会的数学和授权，以反映了nsf的授权，并依靠了nsf的基础。优点和更广泛的影响审查标准。