Microstructure Research Data Workshop at the South Big Data Innovation Hub

本次研讨会将汇集专家，推进微观结构材料科学数据集的公共可访问性和互操作标准，这类数据对材料科学研究的许多领域具有广泛的效用。该研讨会建立在之前的研讨会的基础上，之前的研讨会成功地确定了制造中常用的微观结构描述符中的目标缺口，以关联决定结构性能的合成和宏观特性。本次研讨会旨在确定实现全球分布式和联合微观结构数据互操作性所需的元数据。这些元数据标准的确定和采用将对制造业产生广泛的实际影响，并通过社区参与和建立共识来实现。这次研讨会的成果将有可能极大地推动制造业的发展；有效地开发针对目标结构性能的综合策略，包括对极端环境（如核反应堆和风力发电场）、极端天气条件（海岸侵蚀）、桥梁疲劳和地震破坏的恢复能力。本次研讨会将重点讨论FAIR原则导向的数据管理规范，这些规范在之前的会议中被认为对数据科学企业至关重要，包括：1)元数据管理，2)数据所有权、来源和共享，3)本体和模式等。研讨会将包括多个主题：数据科学教育和劳动力、制造业、团队科学、智慧城市、数据共享和健康差距。此外，材料轨道将延伸到其他轨道，并将：1)弹性城市联系专家,问什么属性在水泥、钢铁、等他们关心并整合的案例研究,2)与专家团队为如何科学有效地执行中标识的可操作的项目研讨会,和3)与员工发展的专家帮助制定一个培训项目数据技术人员在本领域(例如多少数据科学与材料科学技术人员,多少研究人员等需要知道在这个领域工作)。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This workshop will bring together experts to advance public accessibility and interoperation standards for microstructural material science datasets, a category of data that has broad utility for many areas of materials science research. The workshop builds on previous workshops, which succeeded in identifying targeted gaps in microstructure descriptors commonly used in manufacturing to correlate synthesis and macroscopic properties that determine structural performance. This workshop aims at identifying metadata needed to enable interoperability of distributed and federated microstructure data worldwide. The identification and adoption of these metadata standards will have widespread practical impacts in manufacturing, and be pursued through community engagement and consensus building. The results of this workshop will have the potential to dramatically advance manufacturing industries; efficiently developing synthesis strategies towards targeted structural performance, that could include resilience to extreme environments such as nuclear reactors and wind farms, to extreme weather conditions (coastal erosion), to fatigue in bridges, and to earthquake damage.This workshop will focus on FAIR principles-oriented specifications for data management issues that were deemed crucial to the data science enterprise in previous gatherings, including: 1) metadata curation, 2) data ownership, provenance and sharing, 3) ontologies and schema, etc. The workshop will include a number of tracks: Data Science Education and Workforce, Manufacturing, Team Science, Smart Cities, Data Sharing, and Health Disparities. In addition, the materials track will reach out to the other tracks and will: 1) connect with experts in resilient cities and ask what properties in cement, steel, etc. they are concerned with and incorporate those in the case studies, 2) connect with experts in Team Science for advice on how to efficiently execute the actionable items identified in the workshop, and 3) connect with experts in Workforce development for help in crafting a training program for data technicians in this realm (e.g. how much data science and how much materials science would a technician, researcher, etc. need to know to work in this space).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.