一种基于多源数据清洗与融合的高质量海洋观测廓线数据集构建方法OA

[Background]With the development of ocean observation technologies,various marine equip-ment and programs have emerged,propelling research in marine science into a"data-intensive"stage character-ized by big data.[Objective]To integrate heterogeneous ocean observation data from diverse sources into a com-prehensive and unified dataset,thereby enhancing holistic scientific capabilities in addressing marine research questions,this paper proposes a scheme for standardizing,annotating,and cleaning multi-source heterogeneous in situ ocean observation profile data to construct a high-quality ocean observation profile dataset.[Methods]Specifically,the scheme involves acquiring multi-source in-situ ocean observation profile data and corresponding metadata from several ocean data centers/agencies;applying a unique identifier derived from the raw data and de-scriptors to sequentially execute greylist filtering,multi-version filtering,and high-frequency observations filter-ing based on spatiotemporal characteristics,yielding refined ocean observation profile data;standardizing the pro-cessed data,followed by quality control and bias correction to construct a high-quality profile dataset.[Conclu-sions]This scheme promotes the application of multi-source heterogeneous profile data,improving data consis-tency,accuracy,and usability.