CyberTraining: DSE: Cyber Carpentry: Data Life-Cycle Training using the Datanet Federation Consortium Platform

海量数据收集的出现，引领了科学研究和新知识发现方式的范式转变。这种转变要求学生接受以团队为基础的、跨学科的、面向复杂数据的方法的培训，这些方法旨在将科学数据转化为新的解决方案，以促进科学进步；增进国民健康、繁荣和福利，巩固国防。网络基础设施（CI）工具的激增需要从多个角度满足领域科学家的需求，包括数据访问、元数据管理、大规模分析和工作流程、数据和应用程序发现和共享以及数据保存。在工具和解决方案仍然支离破碎的情况下，以这种整体视角进行培训确实令人望而生畏。集成的解决方案，如Datanet Federation Consortium (DFC) Platform，提供了一种缓解这种过载的方法，并帮助触及所有这些需要的功能。该项目的目的是使STEM学科的下一代劳动力更容易学习数据密集型计算环境的各个方面，更重要的是，与其他具有互补专业知识的研究人员一起工作。STEM学科的学生需要接受以下方面的教育：(i)数据组织的实践，（ii）来源、元数据和本体的重要性，（iii）认证、授权和访问控制协议的一致性，（iv）数据共享、发现和管理的模型，(v)可复制数据科学工作流程的必要性，（vi）使用超级计算机和云计算处理大规模数据计算的实践，以及（vii）分布式数据管理实践。Datanet Federation Consortium （DFC）是nsf资助的一个项目，该项目实施了一个以数据为中心的网络平台，该平台集成了端到端数据生命周期管理和数据密集型高性能计算的工具。该项目旨在利用DFC平台，在数据密集型计算环境的各个方面，为STEM研究生提供前沿数据密集型实践方面的培训。他们的培训讲习班将是多学科的，包括地球系统科学、生物科学、社会和信息科学、海洋科学和工程。该项目的短期目标是提供密集的、以学科为中心的短期培训研讨会，称为“网络木匠”。这些研讨会将提供数据科学证书，培养具有高级数据密集型CI能力的更好的科学劳动力。从长远来看，该项目计划开发自定进度的教程和一系列课程，这些课程可以适应不同的STEM学科，重点是数据生命周期管理和数据密集型计算。这些实习将涉及来自多个科学数据存储库的大型数据集，包括几个nsf资助的大型网络基础设施，如iRODS、CyVerse、DataONE、SEAD、TerraPop、DataVerse和HydroShare——所有这些都通过DFC平台集成。项目将从hbcu和msi招收学生参加其研讨会，并将与这些大学的教师密切合作，帮助他们采用通过该项目开发的课程。作为该项目的一部分而开发的所有材料将作为公开课程材料提供。

The emergence of massive data collections has ushered a paradigm shift in the way scientific research is conducted and new knowledge is discovered. This shift necessitates students to be trained in team-based, interdisciplinary, complex data-oriented approaches designed to translate scientific data into new solutions in order to promote the progress of science; to advance the national health, prosperity and welfare, and to secure the national defense. The proliferation of cyberinfrastructure (CI) tools necessitate addressing the needs of domain scientists from multiple angles, including data access, metadata management, large-scale analytics and workflows, data and application discovery and sharing, and data preservation. Training with such a holistic perspective is indeed daunting with a tool and solution landscape that is still fragmented. Integrated solutions, such as the Datanet Federation Consortium (DFC) Platform, provide a way to ease this overload and help touch upon all of these needed functionalities. The aim of this project is to make it easier for next generation workforce in STEM disciplines to learn all aspects of data-intensive computing environment and, more importantly, to work together with other researchers with complementary expertise.Students in STEM disciplines need to be educated in (i) practices of data organization, (ii) importance of provenance, metadata and ontology, (iii) conformance to authentication, authorization and access control protocols, (iv) models for data sharing, discovery and curation, (v) necessity for reproducible data science workflows, (vi) practices in dealing with large-scale data computation using super computers and cloud computing, and (vii) distributed data management practices. The Datanet Federation Consortium (DFC) is an NSF-funded project that has implemented a data-centered cyber platform that has integrated tools for end-to-end data life-cycle management and data-intensive high performance computation. This project aims to use the DFC Platform to provide training for STEM graduate students in leading-edge data-intensive practices, in all aspects of data-intensive computing environments. Their training workshops will be multi-disciplinary, including earth system sciences, biological sciences, social and information sciences, marine sciences and engineering. The short term goal of the project is to provide intensive, short duration training discipline-centric workshops, called Cyber Carpentries. These workshops will lead to Certificates in Data Science, preparing a better scientific workforce with advanced data-intensive CI capabilities. For the long-term, project plans to develop self-paced tutorials and a sequence of courses that can be adapted in different STEM disciplines with concentration in data life-cycle management and data-intensive computing. The practicums will involve large datasets from multiple science data repositories including several NSF-funded large-scale cyberinfrastructure such as iRODS, CyVerse, DataONE, SEAD, TerraPop, DataVerse and HydroShare - all of which are integrated through the DFC Platform. Project will recruit students from HBCUs and MSIs for its workshops and will work closely with faculty from these universities to help them adopt the courses developed through this project. All material developed as part of the project will be made available as open course material.