自然资源要素综合观测质量管理体系构建

自然资源要素综合观测体系具有观测对象多、观测指标多、观测技术手段多等特点。为保证观测数据质量,必须构建覆盖从采集到发布数据全周期全过程的数据质量管理体系。本文针对自然资源要素综合观测对数据质量管理体系提出的新要求,基于国内外观测领域数据质量管理体系现状分析,依据ISO9000族国际标准,建立由目标层、组织层、制度层、控制层及评估层五部分组成的综合观测数据质量管理体系框架;基于模块化集成思维,构建纵横多级质量控制体系：纵向上,建立综合研究中心—一级站—二级站—三级站4级外部检查,横向上,建立观测—校对—审核3级内部检查制度;质控技术上,重点研究了不同观测过程的质控模块,建立了QC0（样品实验测试质量控制模块）、QC1（观测数据内部质量控制模块）、QC2（观测数据外部质量控制模块）、QC3（数据质量的考核和评估模块）4种质控模块,提高了质控针对性和有效性。本文旨在通过构建全面的数据质量管理体系和科学的质控方法,保证观测数据准确可靠。

Construction of the quality management system for comprehensive observation of natural resources

The comprehensive observation system of natural resources has many characteristics, such as multiple objects, indicators, and technical means. In order to ensure the quality of observation data, it is necessary to build a quality management system covering the entire process from collection to publication of data products. Based on the new requirements for a quality management system by the comprehensive observation of natural resources and the analysis of the current situation of quality management systems in the field of observation in China and abroad, this study established a comprehensive observation quality management system framework according to the ISO9001 international standards. The system consists of five parts: target layer, organization layer, regulation layer, control layer, and evaluation layer. Using a modular integration design, this study built a vertical and horizontal multi-level quality control system; established a four-level external inspection process in the vertical direction including the comprehensive center, first level station, second level station, and third level station; and established an observation, proofreading, and review three-level internal inspection process in the horizontal direction. With regard to the quality control technologies, the system focuses on the quality control modules of different observational processes, established four quality control modules: QC0 (sample test quality control module), QC1 (observation data internal quality control module), QC2 (observation data external quality control module), and QC3 (data quality assessment and evaluation module). These modules improve the quality control relevance and effectiveness. By building a comprehensive quality management system and developing scientific quality control methods, this study promotes the long-term and stable development of the comprehensive observation of natural resources.