及时、准确、有价值的农业知识是现代农业农村高质量发展和乡村振兴的重要支撑，亦是各类农业经营主体的迫切需求。由于本体是有效的概念、关系的结构化知识组织工具，开展农情本体的研究是有效解决农业多领域场景化多模态知识需求的基础。现有的农业本体大多是具有较高学科知识体系属性的自顶向下专家决策定义，由于过于注重概念的规范性导致难以直接应用；而部分自底向上构建的本体因为其需求或数据源影响导致具有较为个性化的结构设计，对领域复杂的整体农情领域的本体工作的参考价值不足。因此急需解决农情领域“如何设计具体、面向应用实践且规范完整的本体构建方法”这一科学问题对农情领域本体构建工作具有理论与实践意义。

本文通过研究已有的通用本体研究成果，梳理有效的跨媒体的农业数据获取来源，结合农学、植物学、社会学、哲学等理论与事实案例，提出了一套农情领域完整规范且包含具体技术过程的三级本体映射构建方法。其中三级本体主要包括农情领域顶层本体、农情子领域本体和多模态农情应用本体，通过这三级本体之间的关联映射，实现对农情领域本体构建工作的完整规范定义。主要的研究工作如下:

农情领域的跨领域性和知识复杂性，决定了其很难通过一个本体实现整个领域的知识组织，这就需要一个领域顶层本体为整个领域的本体构建工作提供总体的框架分类与规范。通过研究已有的通用本体和大型农业本体词典的研究成果，梳理农情领域的多模态知识类别，本文设计了一种结合通用本体分类思想和农业本体上层分类框架的农情领域顶层本体构建方法，作为三级本体映射构建方法第一级。通过梳理现有的农情领域内本体构建工作的研究内容，将农情领域的本体构建需求分为提供领域知识服务和指导应用知识库构建两类，基于这两类需求本文分别设计了对应三级本体映射构建方法中的后两级方法，即基于顶层本体的农情子领域本体构建方法与多模态农情应用本体构建方法，作为面向领域内跨模态知识的组织和面向应用背景下跨模态知识的关联两个问题的解决范式。其中农情子领域本体构建方法通过在领域顶层本体中进行概念实例化定位的方式实现前两级本体的关联映射，多模态农情应用本体的构建则通过在农情子领域本体中进行概念选择实现后两级本体的关联映射。

本文在提出本体构建方法的同时，也通过实际数据和研究工作进行了农情领域顶层本体、水稻领域本体、水稻虫害防治多模态应用本体的构建实现，以期望能够对本文描述的构建方法的具体过程进行实践验证，构建的本体也能用于农情领域的本体研究指导。期望后续的领域研究学者能够基于本文章的方法实现农情领域本体的完整规范构建。

Timely, accurate, and valuable agricultural knowledge is an important support for the high-quality development and revitalization of modern agriculture and rural areas, and is also an urgent need for various agricultural management entities. Due to the fact that ontology is an effective structured knowledge organization tool for concepts and relationships, conducting research on agricultural information ontology is the foundation for effectively addressing the multi-domain and multi-modal knowledge needs of agriculture. Most of the existing agricultural ontologies are top-down expert decision-making definitions with high disciplinary knowledge system attributes, which are difficult to directly apply due to excessive emphasis on conceptual standardization; However, some bottom-up constructed ontologies have personalized structural designs due to their requirements or data sources, which have insufficient reference value for the overall ontology work in the complex field of agricultural information. Therefore, it is urgent to solve the scientific problem of "how to design specific, practical oriented, and standardized ontology construction methods" in the agricultural information field, which has theoretical and practical significance for the ontology construction work in the agricultural information field.

This article presents a comprehensive and standardized three-level ontology mapping construction method in the field of agricultural information, which includes specific technical processes, by studying existing research results on general ontology, sorting out effective sources of cross media agricultural data acquisition, and combining theoretical and factual cases in agriculture, botany, sociology, philosophy, and other fields. The three-level ontology mainly includes the top-level ontology of the agricultural information domain, the agricultural information sub domain ontology, and the multimodal agricultural information application ontology. Through the association mapping between these three-level ontologies, a complete and standardized definition of the construction work of the agricultural information domain ontology is achieved. The main research work is as follows:

The cross domain nature and knowledge complexity of the agricultural information field make it difficult to achieve knowledge organization of the entire field through a single ontology. This requires a top-level ontology in the field to provide an overall framework classification and specification for the ontology construction work of the entire field. By studying the research results of existing universal ontologies and large-scale agricultural ontology dictionaries, this paper sorts out the multimodal knowledge categories in the field of agricultural information. This paper designs a top-level ontology construction method in the field of agricultural information that combines the general ontology classification idea and the upper level classification framework of agricultural ontology, as the first level of the three-level ontology mapping construction method. By combing the existing research contents of ontology construction in the field of agricultural information, the ontology construction requirements in the field of agricultural information are divided into two categories: providing domain knowledge services and guiding the construction of application knowledge base. Based on these two categories of requirements, this paper designs the last two levels of corresponding three-level ontology mapping construction methods, namely, the ontology construction method of agricultural information sub domain based on top-level ontology and the ontology construction method of multimodal agricultural information application, As a solution paradigm for the organization of cross modal knowledge in the field and the association of cross modal knowledge in the application context. The construction method of the agricultural information sub domain ontology achieves the association mapping of the first two levels of ontology through concept instantiation and positioning in the top-level ontology of the domain, while the construction of the multimodal agricultural information application ontology achieves the association mapping of the last two levels of ontology through concept selection in the agricultural information sub domain ontology.

While proposing the ontology construction method, this article also implemented the construction of the top-level ontology in the agricultural situation field, the ontology in the rice field, and the multimodal application ontology for rice pest control through actual data and research work. It is hoped that the specific process of the construction method described in this article can be verified in practice, and the constructed ontology can also be used for guiding the ontology research in the agricultural situation field. I hope that future field researchers can achieve a complete and standardized construction of agricultural information domain ontology based on the method proposed in this article.

[1] 薛洲, 高强. 从农业大国迈向农业强国：挑战、动力与策略[J]. 南京农业大学学报(社会科学版), 2023, 23(01): 1-15.
[2] 国家统计局.农业及相关产业统计分类（2020）[S],2022,12(04).
[3] 段宇锋,黄思思.本体构建方法研究[J].情报杂志,2015,34(11):139-144.
[4] 中共中央国务院.关于做好2022年全面推进乡村振兴重点工作的意见[S],2022.
[5] 农业农村部、中央网络安全和信息化委员会办公室.数字农业农村发展规划（2019-2025年）[S],2020.
[6] 中央网信办信息化发展局、农业农村部市场与信息化司.中国数字乡村发展报告（2020年）[R], 2020.
[7] 赵春江.智慧农业发展现状及战略目标研究[J].智慧农业,2019,1(01):1-7.
[8] Gruber T R . A translation approach to portable ontology specifications[J]. Knowledge Acquisition, 1993, 5( 2):199-220.
[9] Gruber T R . Toward principles for the design of ontologies used for knowledge sharing?[J]. International Journal of Human-Computer Studies, 1995, 43( 5–6):907-928.
[10] Sawsaa A, Lu J. Building Information Science ontology (OIS) with Methontology and Protégé [J]. Journal of Internet Technology and Secured Transactions,2012,1(4):100-109.
[11] Song Z H, Zhu F S, Zhang D L, et al. Research on Air and Missile Defense Domain Ontology Development Based on IDEF5 and OWL[J]. Journal of Projectiles, Rockets, Missiles and Guidance,2010,30(1):176-176.
[12] Madni A M, Lin WW, Madni CC. IDEONTM: An extensible ontology for designing, integrating and managing collaborative distributed enterprises[J]. Systems Engineering, 2001, 4(1): 35-48.
[13] Sarder M B, Ferreira S, Rogers J, et al. A Methodology for Design Ontology Modeling[C]. PICMET'07-2007 Portland International Conference on Management of Engineering & Technology. IEEE, 2007.
[14] Gang L, Wang Y, Wu C. Research and application of geological hazard domain ontology[C]. International Conference on Geoinformatics. IEEE, 2010.
[15] 张文秀,朱庆华.领域本体的构建方法研究[J].图书与情报,2011(01):16-19+40.
[16] 杨秋芬, 陈跃新. Ontology方法学综述[J]. 计算机应用研究, 2002(04): 5-7.
[17] 杜文华.本体构建方法比较研究[J].情报杂志,2005(10):24-25.
[18] 李景,孟连生.构建知识本体方法体系的比较研究[J].现代图书情报技术,2004(07):17-22.
[19] 阳广元,刘海英.国内基于本体的知识服务研究进展[J].西南民族大学学报(人文社科版),2017,38(07):237-240.
[20] 岳丽欣,刘文云.国内外领域本体构建方法的比较研究[J].情报理论与实践,2016,39(08):119-125.
[21] Nicola A D，Missikoff M，Navigli R. A Software Engineering Approach to Ontology Building[J]. Information Systems，2009，34(2): 258－275.
[22] 冯兰萍，朱礼军，蒋亚东. 一种模块化本体构建方法研究[J]. 现代图书情报技术，2010(6): 53-59．
[23] Iqbal R , Murad M , Mustapha A , et al. An Analysis of Ontology Engineering Methodologies: A Literature Review[J]. Research Journal of Applied Sciences Engineering & Technology, 2013, 6(16):2993-3000.
[24] Al-Aswadi F N , Chan H Y , Gan K H . Automatic ontology construction from text: a review from shallow to deep learning trend[J]. Artificial Intelligence Review, 2020, 53(6):3901-3928.
[25] Sattar A , Salwana E , Nazir M , et al. Comparative Analysis of Methodologies for Domain Ontology Development: A Systematic Review[J]. International Journal of Advanced Computer Science and Applications, 2020, 11(5).
[26] 李枫林,毛展展.应用本体构建方法研究及案例分析[J].图书馆学研究,2014(19):31-41.
[27] 李勇,张志刚.领域本体构建方法研究[J].计算机工程与科学,2008(05):129-131.
[28] Blomqvist E. Semi - automatic Ontology Construction Based on Patterns[D]. Linkoping: Linkoping University , 2009.
[29] Blomqvist E. Ontology Patterns - Typology and Experiences from Design Pattern Development [C]. Proceedings of the 26th Annual Workshop of the Swedish Artificial Intelligence Society. Uppsala: Linkoping University Electronic Press, 2010.
[30] 李晓辉,孙坦,宋文.本体模式分类研究综述[J].现代图书情报技术,2011(10):1-6.
[31] 李善平,尹奇韡,胡玉杰,郭鸣,付相君.本体论研究综述[J].计算机研究与发展,2004(07):1041-1052.
[32] 杜小勇,李曼,王大治.语义Web与本体研究综述[J].计算机应用,2004(10):14-16+20.
[33] 侯阳,刘扬,孙瑜.本体研究综述[J].计算机工程,2011,37(S1):24-26.
[34] 徐国虎,许芳.本体构建工具的分析与比较[J].图书情报工作,2006(01):44-48.
[35] 李景. 本体理论及在农业文献检索系统中的应用研究——以花卉学本体建模为例[D].中国科学院研究生院（文献情报中心）, 2004.
[36] Su X M，llebrekke L. A comparative study of ontology languages and tools.[2004-09-08]. http://www.idi.ntnu.no/~xiaomeng/pa-per/caise02WorkshopCRC.pdf
[37] 韩婕,向阳.本体构建研究综述[J].计算机应用与软件,2007(09):21-23.
[38] 高凡，李景. Ontology及其与分类法、主题法的关系[J]. 图书馆理论与实践，2005( 2) : 44-46.
[39] 王向前,张宝隆,李慧宗.本体研究综述[J].情报杂志,2016,35(06):163-170.
[40] 张继东，余以胜.利用叙词表构建本体的方法研究[J].图书情报知识，2006( 4) : 82－85.
[41] 米佳.从叙词表到本体的转换研究[J].现代情报,2009,29(01):38-41+48.
[42] 陈立华. 基于OWL 语言设计的网络叙词表本体转化的原理及结构设计分析[J].情报理论与实践，2010( 10) : 113－116.
[43] 纪姗姗，刘峥，宋文.叙词表向本体重构的关键技术研究[J].图书与情报，2013(1) : 8-12.
[44] Harrow I , Balakrishnan R , Jimenez-Ruiz E , et al. Ontology mapping for semantically enabled applications[J]. Drug Discovery Today, 2019, 24(10): 2068-2075.
[45] 段瑞龙,宋文,张士男.基于非本体资源重用重构的本体构建研究[J].情报科学, 2012,30(06):815-819+829.
[46] 吕艳辉,马宗民,王玉喜.基于关系数据库的OWL本体构建方法的研究[J].计算机科学,2009,36(07):153-156+226.
[47] 张玉峰,周磊,王志芳,何超.领域本体构建与可视化展示研究[J].情报理论与实践,2012,35(10):95-98+128.
[48] Chalendar G D, Grau B. SVETLAN' a system to classify nouns in context[C]. International Conference on Ontology Learning. CEUR-WS.org, 2000.
[49] 刘萍,胡月红.领域本体学习方法和技术研究综述[J].现代图书情报技术,2012(01):19-26.
[50] Tao X , Li Y, Ning Z. A Personalized Ontology Model for Web Information Gathering[J]. IEEE Transactions on Knowledge and Data Engineering, 2011, 23(4):496-511.
[51] 李晓辉.本体模式研究综述[J].图书与情报,2013(01):23-29.
[52] 王娜,蒋智慧.动态本体构建的国内外研究现状综述[J].现代情报,2020,40(04):159-166.
[53] 姜颖,黄国彬.国外近两年有关本体研究的进展综述[J].图书馆学研究,2011(14):10-15.
[54] 王翠英. 本体与Folksonomy的比较研究[J]. 图书馆建设, 2008(05): 85-88.
[55] 雷力. 基于folksonomy视觉本体构建的研究[D]. 燕山大学, 2018.
[56] Maillot N , Thonnat M , Boucher A . Towards Ontology Based Cognitive Vision[J]. Machine Vision and Applications, 2004, 16(01): 33-40.
[57] Botorek J , Budikova P , Zezula P . Visual Concept Ontology for Image Annotations, 10.48550/arXiv.1412.6082[P]. 2014.
[58] Giorgis S D, Gangemi A. Introducing ODIN: Ontological Design grounded in Image-schematic kNowledge[C]. 13th Workshop on Ontology Design and Patterns. Hangzhou: 2022.
[59] Tazi S N , Dubey A K , Jain V , et al. Image ontology[C]. Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), 2013 International Conference. 2013.
[60] Poltronieri A, Gangemi A. The music note ontology[C]. Workshop on Ontology Patterns. 2021.
[61] 高桓，漆桂林.动态本体(Dynamic Ontology)[EB/OL].https://zhuanlan.zhihu.com/p/ 30799669，2019－05－03.
[62] 罗钧旻，王蕾. 基于互表性的动态本体体系结构研究[J]. 微电子学与计算机，2013，30 (2) : 124-128.
[63] Chen Y, Xing X. Constructing Dynamic Knowledge Graph Based on Ontology Modeling and Neo4j Graph Database[C]. 2022 5th International Conference on Artificial Intelligence and Big Data (ICAIBD). IEEE, 2022.
[64] Liang A C, Lauser B, Sini M. From AGROVOC to the Agricultural Ontology Service/Concept Server. An OWL model for creating ontologies in the agricultural domain[C]. Dublin Core Conference Proceedings. Dublin Core DCMI, 2006.
[65] 邢平平,施鹏飞,熊范纶.数据挖掘技术在农业数据中的有效应用[J].计算机工程与应用,2001(02):4-6.
[66] Ukpe E. Agriculture Ontology for Sustainable Development in Nigeria[J]. Advances in Computing, 2013, 14(5):57-59.
[67] 刘桂锋, 杨倩, 刘琼.农业科学数据集的本体构建与可视化研究——以“棉花病害防治”领域为例[J].情报杂志,2022,41(09):143-149+175.
[68] 常春. Ontology在农业信息管理中的构建和转化[D].中国农业科学院,2004.
[69] 鲜国建. 农业科学叙词表向农业本体转化系统的研究与实现[D].中国农业科学院,2008.
[70] Xiao-Lu S U, Jing L I, Cui Y P, et al. Review on the Work of Agriculture Ontology Research Group[J]. Journal of Integrative Agriculture, 2012,11(5): 720-730.
[71] 吴霞,曾建勋,吴雯娜.汉语主题词表生物、医学、农业领域顶层本体语义类型框架研究[J].情报科学,2022,40(01):94-101.
[72] 曾桢,陈璟浩,毛进,朱梦娴.贸易信息关联与融合本体研究——以农产品贸易为例[J].情报科学,2021,39(03):120-127+135.
[73] 王超,李书琴,肖红.基于文献的农业领域本体自动构建方法研究[J].计算机应用与软件,2014,31(08):71-74.
[74] 李贯峰,李卫军.基于SWRL的枸杞病虫害本体知识推理研究[J].江苏农业科学,2016,44(11):399-402.
[75] 卜伟琼,方逵,张晓玲,陈益能.基于本体的柑橘病虫害知识模型构建[J].江苏农业科学,2013,41(10):363-366.
[76] 姜大庆,蔡银杰.基于本体的蔬菜病虫害知识库构建[J].江苏农业科学,2012,40(07):368-370.
[77] 郑颖,金松林,张自阳,王斌,茹振钢.基于本体的小麦病虫害问答系统构建与实现[J].河南农业科学,2016,45(06):143-146.
[78] 曹丽英,张晓贤,伞晓辉,陈桂芬.基于本体的玉米病害知识库的构建与集成实现[J].中国农机化,2012(06):85-88.
[79] 李悦,孙坦,鲜国建,赵瑞雪,李娇,黄永文,罗婷婷.面向多源数据深度融合的农作物病虫害本体构建研究[J].数字图书馆论坛,2021(02):2-10.
[80] 徐勇,高雅,刘艳华.农业过程本体及其构建方法——以玉米为例[J].农业网络信息,2009(11):8-11.
[81] 王川,刘尚旺,杨彧昕,段德全.小麦草害本体知识库构建研究[J].河南师范大学学报(自然科学版),2014,42(06):138-142.
[82] Kim, Taehyung, et al. A study of an agricultural ontology model for an intelligent service in a vertical farm[J]. International Journal of Smart Home, 2013, 7(4) : 118-126.
[83] 肖花,刘春年.基于本体的农业灾害应急信息资源目录体系构建研究[J].安徽农业科学,2011,39(24):15147-15149.
[84] 赖英旭,李亚娟,刘静.基于本体的水稻育种方法应用知识库构建[J].北京工业大学学报,2019,45(12):1181-1191.
[85] 郑颖,金松林,张自阳,霍云凤,王斌.基于领域本体的农作物病虫害问题分类研究[J].江苏农业科学,2016,44(09):145-148.
[86] 宗南苏,何绮云,郑业鲁,钱平.农业生产技术本体构建与语义检索实现[J].广东农业科学,2009(03):195-199.
[87] 陈丽娜,方沩,司海平,曹永生.农作物种质资源本体构建研究[J].作物学报,2016,42(03):407-414.
[88] 张伶子,段青玲,李道亮.玉米病虫害诊治本体构建技术研究[J].农机化研究,2012,34(01):41-45.
[89] Yuan-yuan, WEI, and, et al. From Web Resources to Agricultural Ontology: a Method for Semi-Automatic Construction[J]. Journal of Integrative Agriculture, 2012,11(5):775-783.
[90] 苏显新,许文娟,赵洪亮.基于本体的大豆信息服务系统构建与实现[J].湖北农业科学,2012,51(15):3336-3339.
[91] Lagos-Ortiz K , José Medina-Moreira, César Morán-Castro, et al. An Ontology-Based Decision Support System for Insect Pest Control in Crops[C]. Technologies and Innovation: 4th International Conference, CITI 2018. Ecuador: Springer International Publishing, 2018.
[92] 巩如悦. 基于本体的苹果病虫害垂直搜索引擎研发[D].西北农林科技大学,2017
[93] Bansal N, Malik S K. A Framework for Agriculture Ontology Development in Semantic Web[C].2011 International Conference on Communication Systems and Network Technologies. IEEE, 2011
[94] Phonarin P, Nitsuwat S, Haruechaiyasak C. AGRIX: An ontology based agricultural expertise retrieval framework[J]. Advanced Materials Research, 2012, 403: 3714-3718.
[95] 刘峤,李杨,段宏,刘瑶,秦志光.知识图谱构建技术综述[J].计算机研究与发展,2016,53(03):582-600.
[96] 孙瑜. 本体修正[D].中国科学院研究生院（计算技术研究所）,2006.
[97] Neches R，Fikes R E，Gruber T，et al. Enabling Technology for Knowledge Sharing[J]. AI Magazine，1991，12(3) : 36－56.
[98] Genesereth M R, Nilsson N J. Logical Foundations of Artificial Intelligence[J]. Morgan Kaufmann Publishers,Inc, 1987.
[99] Borst W N. Construction of Engineering Ontologies for Knowledge Sharing and Reuse[D]. Ph. D thesis，1997.
[100] Guarino N . Formal Ontology in Information Systems[J]. Proceedings of Fois, 1998.
[101] Studer B，Benjamins V R，Fensel D. Knowledge Engineering: Principles and Methods[J]. Data and Knowledge Engineering，1998，25( 1 /2) : 161－197.
[102] 张晓林，李宇.描述知识组织体系的元数据[J].图书情报工作，2002( 2) : 64-69.
[103] 李景.本体理论在文献检索系统中的应用研究[M]. 北京:北京图书馆出版社，2005: 5-6.
[104] 汤艳莉,赖茂生.Ontology在自然语言检索中的应用研究[J].现代图书情报技术,2005(02):33-36+52.
[105] 张秀兰，蒋玲.本体概念研究综述[J]. 情报学报，2007(4) :527－531.
[106] Gruber T R. Towards Principles for the Design of Ontologies Used for Knowledge Sharing[J]. International Journal of Humancomputer Studies, 1995, 43(5/6): 907-928.
[107] 熊大红,方逵,戴小鹏,黄璜.农业本体构建方法研究[J].农机化研究,2011,33(11):48-51+55.
[108] 图书馆·情报与文献学名词审定委员会. 图书馆·情报与文献学名词[M]. 北京：科学出版社，2019.
[109] Jones D, Benchcapon T, Visser P. Methodologies for ontology development[J]. Capon, 1998: 62-75.
[110] Roxane Ouellet. Uche Ogbuji：Introduction to DAML: Part I [EB/OL]. https://www.xml.com /pub/a/2002/01/30/daml1.html#DAMLHOME
[111] Horrocks I . A denotational semantics for Standard OIL and Instance OIL. 2000.
[112] Tom Hall-Jones. Ontology inference layer oil [EB/OL]. https://tomhalljones.com/web/ ontology-inference-layer-oil/
[113] Sean Bechhofer. Frank van Harmelen. Jim Hendler. et al. OWL Web Ontology Language Reference[S/OL].2004.2(10). https://www.w3.org/TR/owl-ref/#ref-OWL-Overview.
[114] 宋朋.本体映射的研究综述[J].图书馆学研究,2016(14):17-21.
[115] 王顺,康达周,江东宇.本体映射综述[J].计算机科学,2017,44(09):1-10.
[116] 李景. 领域本体的构建方法与应用研究[D].中国农业科学院,2009.
[117] 贾君枝,刘艳玲.顶层本体比较及评估[J].情报理论与实践,2007,(03):397-400.
[118] Hermann Bense. Ontology4.us [EB/OL]. https://www.ontology4.us/Ontology4-Top-Ontology-Mereology.html
[119] 朱彦,郑捷,李晓瑛等.基本形式化本体及其中文版介绍[J].医学信息学杂志,2021,42(01):24-28+60.