The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers whos skills include design and building a knowledge repository, and machine learning researchers who provide expertise on data preparation tasks such as gap filling and advise on different machine learning models that can exploit this data. One of the main goals of the CA20108 cost action is to develop a knowledge portal that is fully compliant with the FAIR principles for scientific data management. In the first year, a bespoke knowledge portal was developed to capture metadata for FAIR datasets. Its purpose was to provide detailed metadata descriptions for shareable \micro data using the WMO standard. While storing Network, Site and Sensor metadata locally, the system passes the actual data to Zenodo, receives back the DOI and thus, creates a permanent link between the Knowledge Portal and the storage platform Zenodo. While the user searches the Knowledge portal (metadata), results provide both detailed descriptions and links to data on the Zenodo platform.

翻译：气候科学数据知识库的开发是一项跨学科工作，需要领域专家（气候科学家）、具备知识库设计与构建技能的数据工程师，以及负责数据准备任务（如空缺填补）并为可利用这些数据的机器学习模型提供建议的机器学习研究人员共同参与。CA20108成本行动的主要目标之一是开发一个完全符合FAIR科学数据管理原则的知识门户。在第一年，我们开发了一个定制化的知识门户，用于捕获FAIR数据集的元数据。其目的是利用WMO标准为可共享的微数据提供详细的元数据描述。该系统在本地存储网络、站点和传感器元数据的同时，将实际数据传送至Zenodo，接收返回的DOI，从而在知识门户与存储平台Zenodo之间建立永久链接。当用户搜索知识门户（元数据）时，结果将同时提供详细描述及指向Zenodo平台数据的链接。