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A Practical Approach to Constructing a Geological Knowledge Graph:A Case Study of Mineral Exploration Data

地球科学学刊:英文版 2023年第5期34卷 1374-1389页

作者： Qinjun Qiu Bin Wang Kai Ma Hairong Lü liufeng tao Zhong Xie Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains Zhengzhou 450046China Key Laboratory of Spatiotemporal Perception and Intelligent Processing Ministry of Natural ResourcesZhengzhou 450046China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Department of Automation Tsinghua UniversityBeijing 100084China

Open data initiatives have promoted governmental agencies and scientific organizations to publish data online for reuse.Research of geoscience focuses on processing georeferenced quantitative data(e.g.,rock parameters,geochemical tests,geophysical surveys and satellite imagery)for discovering new knowledge.Geological knowledge is the cognitive result of human knowledge of the spatial distribution,evolution and interaction patterns of geological objects or processes.Knowledge graphs(KGs)can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently.In this paper,we propose a novel framework that can extract the geological knowledge graph(GKG)from public reports relating to a modelling study.Based on the analysis of basic questions answered by geology,we summarize and abstract geological knowledge elements and then explore a geological knowledge representation model with three levels of“geological conceptsgeological entities-geological relations”to describe semantic units of geological knowledge and their logic relations.Finally,based on the characteristics of mineral resource reports,the geological knowledge representation model oriented to“object relationships”and the hierarchical geological knowledge representation model oriented to“process relationships”are proposed with reference to the commonly used geological knowledge graph representation.The research in this paper can provide some implications for the formalization and structured representation of geological knowledge graphs.

关键词： mineral resource report geological knowledge knowledge graph ontology hierarchical knowledge representation model

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Extracting Named Entity Using Entity Labeling in Geological Text Using Deep Learning Approach

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地球科学学刊:英文版 2023年第5期34卷 1406-1417页

作者： Qinjun Qiu Miao Tian Zhong Xie Yongjian Tan Kai Ma Qingfang Wang Shengyong Pan liufeng tao State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR Chinese Academy of Surveying and MappingBeijing 100036China Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghai 20063China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Chengdu Geological Environment Monitoring Station Chengdu 610036China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Artificial intelligence(AI) is the key to mining and enhancing the value of big data, and knowledge graph is one of the important cornerstones of artificial intelligence, which is the core foundation for the integration of statistical and physical representations. Named entity recognition is a fundamental research task for building knowledge graphs, which needs to be supported by a high-quality corpus, and currently there is a lack of high-quality named entity recognition corpus in the field of geology, especially in Chinese. In this paper, based on the conceptual structure of geological ontology and the analysis of the characteristics of geological texts, a classification system of geological named entity types is designed with the guidance and participation of geological experts, a corresponding annotation specification is formulated, an annotation tool is developed, and the first named entity recognition corpus for the geological domain is annotated based on real geological reports. The total number of words annotated was 698 512 and the number of entities was 23 345. The paper also explores the feasibility of a model pre-annotation strategy and presents a statistical analysis of the distribution of technical and term categories across genres and the consistency of corpus annotation. Based on this corpus, a Lite Bidirectional Encoder Representations from Transformers(ALBERT)-Bi-directional Long Short-Term Memory(BiLSTM)-Conditional Random Fields(CRF) and ALBERT-BiLSTM models are selected for experiments, and the results show that the F1-scores of the recognition performance of the two models reach 0.75 and 0.65 respectively, providing a corpus basis and technical support for information extraction in the field of geology.

关键词： ontology geological reports named entity recognition geological corpus construction semi-automated annotation platforms deep learning

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Knowledge Graph for Identifying Geological Disasters by Integrating Computer Vision with Ontology

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地球科学学刊:英文版 2023年第5期34卷 1418-1432页

作者： Qinjun Qiu Zhong Xie Die Zhang Kai Ma liufeng tao Yongjian Tan Zhipeng Zhang Baode Jiang School of Computer Science China University of GeosciencesWuhan 430078China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China National Engineering Research Center of Geographic Information System Wuhan 430074China School of Resource and Environmental Sciences Wuhan UniversityWuhan 430074China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China

The occurrence of geological disasters can have a large impact on urban safety. Protecting people’s safety is the most important concern when disasters occur. Safety improvement requires a large amount of comprehensive and representative risk analysis and a large collection of information related to geological hazards, including unstructured knowledge and experience. To address the relevant information and support safety risk analysis, a geological hazard knowledge graph is developed automatically based on computer vision and domain-geoscience ontology to identify geological hazards from input images while obeying safety rules and regulations, even when affected by changes. In the implementation of the knowledge graph, we design an ontology schema of geological disasters based on a top-down approach, and by organizing knowledge as a logical semantic expression, it can be shared using ontology technologies and therefore enable semantic interoperability. Computer vision approaches are then used to automatically detect a set of entities and attributes, using the data from input images, and object types and their attributes are identified so that they can be stored in Neo4j for reasoning and searching. Finally, a reasoning model for geological hazard identification was developed using the Neo4j database to create nodes, relationships, and their properties for modeling, and geological hazards in the images can be automatically identified by searching the Neo4j database. An application on geological hazard is presented. The results show the effectiveness of the proposed approach in terms of identifying possible potential hazards in geological hazards and assisting in formulating targeted preventive measures.

关键词： geological hazard computer vision knowledge graph city safety ontology

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Integrating NLP and Ontology Matching into a Unified System for Automated Information Extraction from Geological Hazard Reports

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地球科学学刊:英文版 2023年第5期34卷 1433-1446页

作者： Qinjun Qiu Zhen Huang Dexin Xu Kai Ma liufeng tao Run Wang Jianguo Chen Zhong Xie Yongsheng Pan Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Beijing Key Laboratory of Urban Spatial Information Engineering Beijing 100045China School of Geography and Information Engineering China University of GeosciencesWuhan 430074China Wuhan Geomatics Institute Wuhan 430074China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China Geological Environmental Center of Hubei Province Wuhan 430034China Faculty of Earth Resources China University of GeosciencesWuhan 430074China State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430078China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Many detailed data on past geological hazard events are buried in geological hazard reports and have not been fully utilized. The growing developments in geographic information retrieval and temporal information retrieval offer opportunities to analyse this wealth of data to mine the spatiotemporal evolution of geological disaster occurrence and enhance risk decision making. This study presents a combined NLP and ontology matching information extraction framework for automatically recognizing semantic and spatiotemporal information from geological hazard reports. This framework mainly extracts unstructured information from geological disaster reports through named entity recognition, ontology matching and gazetteer matching to identify and annotate elements, thus enabling users to quickly obtain key information and understand the general content of disaster reports. In addition, we present the final results obtained from the experiments through a reasonable visualization and analyse the visual results. The extraction and retrieval of semantic information related to the dynamics of geohazard events are performed from both natural and human perspectives to provide information on the progress of events.

关键词： geological hazard report spatiotemporal information geological hazard ontology natural language processing gazetteers onlology machine learning

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地球表层系统开放科学数据目录关联网络构建研究进展

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地球信息科学学报 2024年第4期26卷 866-880页

作者：邱芹军郝孟璂谢忠陶留锋李伟杰王洋刘建东中国地质大学(武汉)计算机学院武汉430074 地理信息系统国家地方联合工程实验室武汉430074 中国地质大学(武汉)地质探测与评估教育部重点实验室武汉430074

快速发现、挖掘并利用海量地球表层系统(以下简称“地表系统”)开放科学数据,是大数据时代下地表系统开放科学数据共享新的发展趋势和前沿研究方向。地表系统开放科学数据具有组织分散、多源异构、多模态、多类型等特性,通常以专题共享... 详细信息

快速发现、挖掘并利用海量地球表层系统(以下简称“地表系统”)开放科学数据,是大数据时代下地表系统开放科学数据共享新的发展趋势和前沿研究方向。地表系统开放科学数据具有组织分散、多源异构、多模态、多类型等特性,通常以专题共享网站、数据服务、元数据、期刊论文(特别是数据论文)等形式存在,研究发展适应不同模态的地表系统开放数据挖掘方法、分析其共享质量是充分利用这些数据的关键科学问题。关联网络为地表系统开放科学数据的语义互联和知识发现提供了有力的支撑,其以元数据URI(Uniform Resource Identifier)为节点,元数据间的语义关系为边,节点间关联性的强弱作为边的值。本文从地表系统开放科学数据关联网络构建角度出发,对其发展现状、基本特征和构建技术进行了调研与分析。首先选取国内外典型关联网络和相关文献作为研究对象,根据所选取的9个主流关联网络和200余篇相关文献,从关联网络的基本特征和构建技术2个方面进行比较分析。在基本特征方面,分析了关联网络的数据来源、自动化程度和更新方式;在构建技术方面,介绍了关联指标的选择,讨论了地表系统开放科学数据特征的提取、表示和计算方法。最后提出了未来地表系统关联网络构建的建议,包括构建高质量、全覆盖的地表系统开放科学数据本体、考虑顾及“时间-空间-内容”地学知识复杂关系及推理、建立面向多语言的地表系统开放科学数据关联网络方法以及提升地表系统开放科学数据关联网络应用成效等。

关键词：地球表层系统关联网络数据目录特征计算元数据共享程度评价数据本体关联指标

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面向地质图的知识图谱构建及智能问答应用

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地质科学 2024年第2期59卷 588-602页

作者：段雨希邱芹军田苗马凯谢忠陶留锋刘俊杰国家地理信息系统工程技术研究中心武汉430074 中国地质大学(武汉)计算机与信息学院武汉430074 地理信息系统国家地方联合工程实验室武汉430074 中国地质大学(武汉)地质探测与评估教育部重点实验室武汉430074 三峡大学计算机与信息学院湖北宜昌430002 湖北省水电工程智能视觉监测重点实验室湖北宜昌443002

海量地质图件蕴含着丰富的地学基础知识及专家经验知识。地质图主要表达了通过区域地质调查、矿产地质调查所获取的地球表面的地质知识(如地层单元、岩体、断裂等)。如何快速地从矢量地质图件中抽取地质知识并形成知识服务是目前地学知... 详细信息

海量地质图件蕴含着丰富的地学基础知识及专家经验知识。地质图主要表达了通过区域地质调查、矿产地质调查所获取的地球表面的地质知识(如地层单元、岩体、断裂等)。如何快速地从矢量地质图件中抽取地质知识并形成知识服务是目前地学知识图谱及知识服务研究的前沿。由于传统的地质图知识抽取主要依赖人工方式进行综合分析,本文聚焦于矢量地质图件知识表达与抽取研究,提出了一种地质图知识表达框架,提取地质图中所包含的地质实体及关系,将地质图信息以知识图谱的形式表达,并开展了基于地质矢量知识图谱的智能问答应用。最后以江西省于都县银坑幅矢量数据集为例开展实验验证分析,结果表明,本文方法能够较为全面地获取地质图中各个地质对象的信息,提高了地质图语义表达的效果,同时也可以提高地质学习人员对地质图的理解和认识,让计算机能够大规模获取地质图的知识内容。

关键词：地质图知识表达模型地质知识图谱地质矢量图件智能问答空间认知

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Cloud-Based Spatial Information Service Architecture within LBS

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Positioning 2014年第3期5卷 59-65页

作者： Tingyan Xing Shang Zhang liufeng tao Faculty of Information Engineering China University of Geosciences Beijing China

Location Based Services (LBS) have become a popular technology to retrieve information about the surroundings of a mobile user which results in ubiquitous demand of spatial information service with diverse needs of different types of users. The aim of this paper is to reveal the potential of cloud-based spatial information service architecture that plays an integral role in LBS design and practice. This paper analyzes the characteristics of the spatial information of cloud services, such as data access transparency, spatial analysis parallelization, service capabilities flexible, information services standardization, service aggregation visualization, re-development flexible. This paper provides a possible solution to overcome the LBS service issues. In this paper, the short review of LBS and Cloud computing are given first and then the possibility of LBS design with cloud computing are analyzed. At last, cloud-based spatial information service architecture is proposed.

关键词： Cloud Computing Spatial Information Cloud Services LBS Introduction

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基于生物信息学分析胃肠上皮化生关键基因及靶向中药

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中医学报 2024年第5期39卷 1082-1090页

作者：易柳凤陶思羽李萌王少丽刘震北京中医药大学北京100029 中国中医科学院广安门医院北京100053

目的:基于生物信息学方法分析胃肠上皮化生(intestinal metaplasia,IM)的关键基因、机制通路,并预测潜在靶向中药。方法:从GEO数据库获取GSE78523、GSE60427数据集,利用GEO2及R软件筛选IM差异表达基因并对其进行富集分析,通过STRING数... 详细信息

目的:基于生物信息学方法分析胃肠上皮化生(intestinal metaplasia,IM)的关键基因、机制通路,并预测潜在靶向中药。方法:从GEO数据库获取GSE78523、GSE60427数据集,利用GEO2及R软件筛选IM差异表达基因并对其进行富集分析,通过STRING数据库和Cytoscape软件构建蛋白互作网络(protein-protein interaction,PPI),筛选关键基因,利用Kaplan-Meier Plotter数据库、GEPIA数据库及HPA数据库对关键基因进行生存分析及表达验证,在Coremine Medical数据库预测筛选潜在中药。结果:筛选出285个差异表达基因。基因本体功能富集分析显示,差异基因主要参与消化吸收、肠道脂质的调节与吸收等生物过程。京都基因和基因组百科全书通路富集分析主要涉及营养物质的消化和吸收、糖酵解/糖异生、胆汁分泌、胆固醇代谢等。获取的7个关键基因是APOB、FABP1、APOA1、APOA4、NR1H4、PCK1、ALDOB。筛选得到的潜在中药可分为健脾益气和胃、祛瘀通络、解毒祛邪三大类,符合胃IM健脾通络解毒的治则。结论:本研究筛选出7个与IM密切相关的核心基因,挖掘出可能用于胃癌前病变靶向治疗的中药。

关键词：胃肠上皮化生基因靶向中药生物信息学

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基于数据湖技术的地质大数据底座架构研究与应用

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自然资源信息化 2024年第2期 43-49,68页

作者：黄家凯秦丽娟郑诗语邱芹军陶留锋湖北省地质调查院湖北武汉430034 中国地质大学(武汉)计算机学院湖北武汉430070

地质数据是经济社会发展的上游要素,具有非常重要的价值。当前,地质大数据研究存在数据底座与应用系统未解耦、数据即服务(Data as a Service,DaaS)未充分厘清的问题,这导致地质数据的可复用性差。本文在系统应用数据湖技术的基础上,聚... 详细信息

地质数据是经济社会发展的上游要素,具有非常重要的价值。当前,地质大数据研究存在数据底座与应用系统未解耦、数据即服务(Data as a Service,DaaS)未充分厘清的问题,这导致地质数据的可复用性差。本文在系统应用数据湖技术的基础上,聚焦多源、异构、海量、时空相关地质数据的汇聚、治理与服务,研究提出基于数据湖技术的地质大数据底座架构,设计由数据采集与清洗层、数据存储层、数据计算与分析层、数据服务层、数据治理层构成的技术架构,并对部分关键技术选型进行验证,为地质大数据中心建设工程提供实践参考。

关键词：地质数据湖地质大数据数据底座数据汇聚数据服务

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面向灾害应急响应的地质灾害链知识图谱构建方法

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地球科学 2023年第5期48卷 1875-1891页

作者：邱芹军吴亮马凯谢忠陶留锋中国地质大学计算机学院湖北武汉430078 三峡大学计算机与信息学院湖北宜昌443002 湖北省水电工程智能视觉监测重点实验室湖北宜昌443002 湖北省农田环境监测工程技术研究中心湖北宜昌443002

知识图谱是形式化描述实体及其相互关系的知识系统,其在应急救灾、时空预测决策等方面发挥着重要的作用.灾害应急领域面临数据骤增而应急关键知识匮乏问题,由此从灾害链角度分析地质灾害发展过程中关联的诸多要素,提出了一种自顶向下和... 详细信息

知识图谱是形式化描述实体及其相互关系的知识系统,其在应急救灾、时空预测决策等方面发挥着重要的作用.灾害应急领域面临数据骤增而应急关键知识匮乏问题,由此从灾害链角度分析地质灾害发展过程中关联的诸多要素,提出了一种自顶向下和自底向上结合的地质灾害链知识图谱构建方法.首先,基于灾害链角度对地质灾害间复杂形成机理及成链规律进行分析,在已有地质灾害知识基础上,基于自顶向下方法建立了统一的用于信息抽取的地质灾害链本体语义表达框架,包括描述地质灾害知识体系的地质灾害事件本体、承载地质灾害发生的地质环境本体、受地质灾害作用下的地理对象本体及地质灾害在灾前、灾中和灾后时空过程中对应的应急处置方法本体;其次,结合自底向上方法构建数据层,通过知识融合、知识存储对概念、实例与属性等要素及其关联关系进行识别;最后以汶川地震为例并对知识图谱进行可视化表达.结果表明,本方法能有效地对四类要素及其关系进行识别,实现了数据‒信息‒知识的转换,为地质灾害领域的知识图谱构建提供技术参考.

关键词：地质灾害链知识图谱领域本体自然语言处理应急响应灾害地质.

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