| With the rapid development and widespread use of information paradigms such as the Semantic Web and WEB4.0,new forms of information resource organisation,dissemination and utilisation are being formed,and are profoundly affecting the various implementation methods and effects of industrial informatisation,and agricultural informatisation is also influenced by this trend to usher in rapid development.As an important part of the development of agricultural informatization,agricultural machinery,in the face of the increasingly urgent demand for professional and intelligent knowledge services shown by users,how to make use of modern information technology to carry out in-depth organization,correlation and mining analysis of knowledge resources in professional fields and provide deep-level,high-quality knowledge services for scientific research has become an important issue facing professional information resource construction and service institutions such as intelligence In this context,this paper focuses on the agricultural information resources.In this context,this paper takes agricultural machinery knowledge resources as an example and introduces the technology of Linked Data to explore the organisation of knowledge and knowledge discovery and application in the field of agricultural machinery.Linked data is an implementation of the semantic web,and its features such as dynamic extension of data sources,knowledge meta-association and semantic retrieval of knowledge provide new ideas to change the situation of non-dynamic update,weak visualisation and semantic scarcity faced in the traditional knowledge organisation process.This study first investigates the current research status of knowledge organisation at home and abroad and the hot topics in the application of Linked Data to knowledge organisation from both macro and micro perspectives,and clarifies the research lineage by means of literature research and bibliometric methods.Secondly,an agricultural machinery domain ontology is constructed for the semanticization of knowledge resource entities according to the characteristics of agricultural machinery knowledge resources,and the evolution of domain ontology is studied.Meanwhile,relying on literature and intelligence resources such as journal papers and scientific data,the core concepts of knowledge resources are revealed through entity extraction and ontology mapping.Subsequently,based on the theory of Linked Data knowledge,a semantic model of agricultural machinery knowledge resources is designed,and a knowledge resource publication process with reference to the four principles of Linked Data is proposed.With the help of theoretical models and auxiliary tools,Linked Data generation and publication of collected domain concepts,relationships and attribute RDFs are carried out,and the linking and aggregation between different Linked Data sets are investigated.Finally,the theoretical and practical values of the organisation of agricultural machinery knowledge resources based on Linked Data are verified in terms of both academic theory and practical application;knowledge interconnection and cross-domain knowledge discovery of journal papers and scientific data are realised in the practical domain;in the academic domain,a three-dimensional interdisciplinary measurement of the agricultural machinery domain is realised based on the Linked Data resources of academic journals,combined with disciplinary intersection and information theory.This study uses Linked Data and other technologies to semantically express and organise knowledge in the field of agricultural machinery,organise and manage scattered knowledge resources in a unified manner,realise the association and integration of domain information resources and disciplinary literature resources,and at the same time construct a personalised knowledge service platform to provide basic support for the construction of a thematic knowledge base in the field of agricultural machinery,enhance the effectiveness and efficiency of knowledge services in the field of agricultural machinery,and expand the scope of application of knowledge resources.It will expand the application scope of knowledge resources and provide more comprehensive and accurate data support for agricultural research. |
