FAIR: a project to realize a user-friendly exchange of open weather data

Q2 Earth and Planetary Sciences Advances in Science and Research Pub Date : 2020-09-18 DOI:10.5194/ASR-17-183-2020
C. W. Frank, F. Kaspar, J. Keller, Till Adams, Miriam Felkers, B. Fischer, M. Handte, P. Marrón, Hinrich Paulsen, M. Neteler, J. Schiewe, Marvin Schuchert, C. Nickel, R. Wacker, Richard Figura
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引用次数: 4

Abstract

Abstract. Access to high quality weather and climate data is crucial for a wide range of societal and economic issues. It allows optimising industrial processes, supports the identification of potential risks related to climate change or allows the development of corresponding adaptation and mitigation strategies. Although such data is freely available through Germany’s national meteorological service DWD (Deutscher Wetterdienst) since 2017, the application potential in industry and society has certainly not yet been fully unlocked. Major obstacles are the complexity of the raw data, as well as missing tools for their simple integration into existing industrial applications. The goal of the research project FAIR is to simplify the information exchange between the DWD and economical players. In order to reach this goal a requirement analysis with end-users of weather data from three different sectors was conducted. A central requirement regarding the site assessment of wind plants is quick and easy access to historical wind-series at specific sites. Preferably downloadable in formats like CSV or via an API. Event planning partners are interested in a quick access to health relevant weather information at their event location, and the E-mobility sector in temperature data along planned routes. In this paper, we summarize the results of the requirement analysis and present the deduced technical architecture and FAIR services aiming at a user-friendly exchange of weather data.
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FAIR:一个实现开放天气数据的用户友好交换的项目
摘要获取高质量的天气和气候数据对于广泛的社会和经济问题至关重要。它有助于优化工业流程,支持识别与气候变化有关的潜在风险,或有助于制定相应的适应和缓解战略。尽管自2017年以来,这些数据已通过德国国家气象服务机构DWD (Deutscher weterdienst)免费提供,但在工业和社会中的应用潜力肯定尚未完全释放。主要障碍是原始数据的复杂性,以及缺少将其简单集成到现有工业应用程序中的工具。研究项目FAIR的目标是简化DWD与经济参与者之间的信息交换。为了达到这个目标,我们对来自三个不同界别的天气数据的最终用户进行了需求分析。关于风电场选址评估的一个核心要求是快速方便地获取特定地点的历史风力序列。最好以CSV或通过API等格式下载。活动规划合作伙伴希望在其活动地点快速获取与健康相关的天气信息,而电动交通部门则希望获得计划路线沿线的温度数据。在本文中,我们总结了需求分析的结果,并提出了推导的技术架构和FAIR服务,旨在实现用户友好的天气数据交换。
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来源期刊
Advances in Science and Research
Advances in Science and Research Earth and Planetary Sciences-Geophysics
CiteScore
4.10
自引率
0.00%
发文量
13
审稿时长
22 weeks
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