数据与计算发展前沿2026，Vol.8Issue(3)：68-80,13.DOI:10.11871/jfdc.issn.2096-742X.2026.03.007
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
A High-Quality Ocean Observation Profile Datasets Construction Scheme Based on Multi-Source Data Cleaning and Fusion
摘要
Abstract
[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.关键词
海洋大数据/数据清洗/海洋观测/数据集Key words
ocean big data/data clean/ocean observation/datasets引用本文复制引用
原惠峰,朱雨静,潘玉莹,张荣望,金钟..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[J].数据与计算发展前沿,2026,8(3):68-80,13.基金项目
亚洲合作资金项目(102173250600000000010) （102173250600000000010）
国家重点研发计划(2023YFB3001900) （2023YFB3001900）
