WaterSciCon24 Workshop Materials: Advancing Open Data Science and Analytics for Water

Water science and management challenges require synthesis of diverse data. Many data analysis tasks are difficult because data are large or complex; standard formats are not always agreed upon or mapped to efficient structures for analysis; scientists may lack training for tackling large and complex datasets; and it can be difficult to share, collaborate around, and reproduce scientific work. Access to computing for running and sharing data science or modeling workflows and structuring them in a way that they can be reproduced can also be challenging. Overcoming these barriers can transform the way water scientists work. Participants will learn how to use multiple data science tools, including data retrieval packages for easy access to data from the United States Geological Survey’s (USGS) National Water Information System (NWIS) and tools associated with the CUAHSI HydroShare repository and linked JupyterHub environment available to assist scientists in building, sharing, and publishing more reproducible scientific workflows following Findable, Accessible, Interoperable, and Reusable (FAIR) principles. We will demonstrate how the technical burden for scientists associated with creating a computational environment for executing analyses can be reduced and how sharing and reproducibility of analyses can be enhanced through the use of these tools. This HydroShare resource includes all of the materials presented in a workshop at WaterSciCon24.水科学与管理领域的诸多核心挑战，亟需对多源异构数据开展综合集成分析。诸多数据分析任务面临困境，其成因主要包括：数据体量庞大或结构复杂；数据分析尚未形成统一标准格式，亦未映射至高效的分析结构框架；科研人员可能缺乏处理大规模复杂数据集的相关训练；此外，科研成果的共享、协作与复现亦存在较高门槛。同时，搭建可复现的数据科学或建模工作流所需的计算资源访问权限，以及此类工作流的结构化部署，同样是一项突出挑战。攻克上述壁垒，将彻底重塑水科学研究者的工作模式。 参训学员将学习如何使用多款数据科学工具：其中包括用于便捷获取美国地质调查局（United States Geological Survey, USGS）国家水信息系统（National Water Information System, NWIS）数据的检索工具包，以及适配CUAHSI HydroShare知识库与关联JupyterHub环境的相关工具。上述工具可辅助科研人员遵循可发现、可访问、可互操作、可复用（Findable, Accessible, Interoperable, and Reusable, FAIR）原则，构建、共享并发布更具复现性的科研工作流。本次培训将演示，如何通过使用此类工具，降低科研人员搭建数据分析计算环境所需的技术负担，并提升数据分析成果的共享性与复现性。 本HydroShare资源包含了WaterSciCon24研讨会的全部授课材料。