面向航天装备大数据的知识图谱体系

近年来，航天装备大数据平台建设已经取得了长足进步。然而，航天装备数据深层次价值仍然未被有效发掘，关键原因在于现有大数据业务数据存在无法跨专业贯通、缺乏全局数据资源智能分析及管理。知识图谱技术作为大数据时代的推理和分析利器，与航天装备大数据完成无缝对接具有天然的优势和内在动机。本文从研究面向航天装备数据知识图谱的/组织管理、关联分析、数据挖掘、知识可视化等开放式共享服务出发，通过大数据、人工智能方法挖掘航天数据的应用潜力，并引入数据化决策模型和监控体系，建立航天装备数据全息画像，实现业务数据的跨业务贯通，并提供网格化的高速检索，以求通过提升数据管理的规范化、标准化、精益化水平指导航天装备的优化和升级。

Knowledge map system of big data platform for aerospace equipment

Significant progress has been made in the construction of big data platforms for aerospace equipment in recent years. However, the deep-seated value of data on aerospace equipment still cannot be effectively explored because currently available big data cannot be integrated across disciplines and there is a lack of intelligent analysis and management of global data resources. As a powerful tool for reasoning and analysis in the era of big data, knowledge mapping has natural advantages in terms of seamlessly being applied to big data on aerospace equipment. This study examines open sharing services related to organization and management, association analysis, data mining, and knowledge visualization in the context of creating a knowledge atlas for data on aerospace equipment. It also examines unifying metadata standards, data integration, data cleaning, the governance and application of aerospace data in various fields, excavating the applicative potential of such data through Artificial Intelligence, and introducing a data-based decision-making model and monitoring system. This system can provide high-speed grid retrieval, improve standardization and data management, and guide the optimization and upgrade of aerospace equipment.