Collaborative Conference: A Workshop to Explore Data Science in Oceanography

合作会议：探索海洋学数据科学的研讨会

• 批准号: 2038846
• 负责人: Nicholas Record
• 金额: $ 0.74万
• 依托单位: Bigelow Laboratory for Ocean Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038846&HistoricalAwards=false
• 关键词: Collaborative; Conference; Workshop; Explore; Data

Computational and data science skills have become essential in making scientific discoveries, especially in fields where the integration of diverse sources of observational and modeled data is required to understand the mechanisms and functions of complex systems, such as the Earth’s ocean. However, conventional ocean sciences education focuses predominantly on domain-specific knowledge and often falls short in explicitly incorporating these operational skills into the curriculum. The PIs will plan and host several workshops, a virtual workshop in 2020 and two in-person workshops in 2021, that aim to address this urgent need by combining immersive tutorials on state-of-the-art data science methodologies, peer-learning, and on-site collaborative hack project work in a 5-day intensive workshop. This is a domain-specific adaptation of the “hackweek” model, which has emerged in the computational data science community as a powerful model for educating new users, sharing technical expertise, and building an inclusive and cohesive community. The focus of the workshops is the use of ocean data, and specifically the use of data from the NSF-funded Ocean Observatories Initiative. The workshops, called "OceanHackWeek2020-2021", provide an avenue for expediting the adoption of data science methodologies and computational tools for data-intensive research in the ocean sciences community. These skills are indispensable for modern-day oceanographers to tackle complex scientific questions by harnessing the data revolution. OceanHackWeek differs from traditional academic conferences and one-off hackathons by its immersive curriculum, collaborative learning environment, and a set of carefully crafted participant selection criteria that helps promote diversity and inclusivity. These designs help spur collaborative interdisciplinary ideas and help promote best data science practices in ocean sciences. OceanHackWeek focuses not only on promoting data science literacy but also on building an inclusive and cohesive community of oceanographers for learning and sharing. The organizers encourage and empower participants to bring the skills gained and the sense of community formed during the hackweek back to their own labs and institutions. Beyond the intensive in-person workshop, OceanHackWeek tutorials will be maintained as persistent open online resources to allow anyone to partake and self-learn. By facilitating and catalyzing the growth and change of individuals through grassroot efforts that promote and embrace a diverse community, OceanHackWeek drives cultural change in the field of oceanography.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.

计算机和数据科学技能对于使科学发现的观察和建模数据至关重要，但是我需要对竞争系统的机制和功能进行建模数据，但是，通俗的海洋科学教育主要集中在特定领域的特定领域，而Olls则在明确的情况下将这些操作技能纳入游览中。 Riculum。在5天的密集研讨会上，这是“ hackweek”模型的域名改编，该模型已在计算数据科学中作为一个有力的模型，用于教育新用户的焦点和凝聚力。是cean数据的使用，以及来自NSF资助的观察者的UFE，称为“ OceanHackweek 2020-2021”的工作坊。为了利用数据革命来解决复杂的科学家，以解决复杂的科学。 。作为持续的在线资源，任何人都可以通过促进和促进个人个人的成长和变化来参加和自学。使用基金会的智力优点和更广泛的影响审查标准，剥夺了支持的thalu ation。