Review on the Work of Agriculture Ontology Research Group

Su, Xiaolu; Li, Jing; Cui, Yunpeng; Meng, Xin; Wang, Yiqian

doi:10.1016/s2095-3119(12)60061-6

Cited by 3 publications

(3 citation statements)

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“…Our literature review reveals that in the context of agriculture, ontologies are used for four main purposes: As means to share vocabularies and integrate data (e.g., [6,18]), for knowledge search and exploration [17][18][19]21,25,33], for system interoperability (e.g., [20,22,30]), and for decision support and automation (e.g., [32,50]). The evaluation of ontologies with these different purposes requires focusing on different ontology aspects, i.e., it calls for the evaluation of different ontology levels: the lexical, vocabulary, or data level, the hierarchy or taxonomy level, the semantic relations level (other than hierarchical), and the context level [44].…”

Section: Proposed Framework For Agricultural Ontology Evaluationmentioning

confidence: 99%

“…The increasing use of ontologies is also seen in agriculture (e.g., [4,6,[17][18][19][20][21][22][23][24][25][26]), where they are used for various purposes, such as agriculture knowledge sharing across farmers around the world and in different languages [18,25,[27][28][29], creating semantic interoperability of agricultural systems [4,22,30,31], and supporting farmer decisions [32] by providing automatic knowledge inference. This is not surprising, given that agriculture is a knowledge-centric field that covers many areas of expertise and many world-wide used practices and technologies.…”

Section: Introductionmentioning

confidence: 99%

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A Framework for Evaluating Agricultural Ontologies

2021

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An ontology is a formal representation of domain knowledge, which can be interpreted by machines. In recent years, ontologies have become a major tool for domain knowledge representation and a core component of many knowledge management systems, decision-support systems and other intelligent systems, inter alia, in the context of agriculture. A review of the existing literature on agricultural ontologies, however, reveals that most of the studies, which propose agricultural ontologies, are lacking an explicit evaluation procedure. This is undesired because without well-structured evaluation processes, it is difficult to consider the value of ontologies to research and practice. Moreover, it is difficult to rely on such ontologies and share them on the Semantic Web or between semantic-aware applications. With the growing number of ontology-based agricultural systems and the increasing popularity of the Semantic Web, it becomes essential that such evaluation methods are applied during the ontology development process. Our work contributes to the literature on agricultural ontologies by presenting a framework that guides the selection of suitable evaluation methods, which seems to be missing from most existing studies on agricultural ontologies. The framework supports the matching of appropriate evaluation methods for a given ontology based on the ontology’s purpose.

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Section: Proposed Framework For Agricultural Ontology Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Framework for Evaluating Agricultural Ontologies

2021

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“…It is a first of its kind developed in China, using data from Chinese Agricultural Scientific & Technological Document Database. [17] 2…”

Section: Chinamentioning

confidence: 99%

An Exploratory Study on Agriculture Ontology: A Global Perspective

Jebaraj¹,

Sathiaseelan²

2017

IJARCSSE

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Abstract-Ontologies have played a vital role in the field of agriculture. The agriculture domain is a vast and complex system science and the knowledge of it consists of many concepts and relationships. These difficult concepts and relationships have been modelled using Ontologies in various capacities in different countries. This paper is an exploratory study, presenting a review on the various ontology-based applications developed specifically in the domain of agriculture. It also discusses the various Agriculture Ontologies created by specific developing countries. Finally this paper also summarizes the directions for future work.

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Methods for building ontologies to ensure coordinated behavior of autonomous intellectual systems in agriculture

Bzhikhatlov,

Pshenokova,

Nagoeva

2024

BIO Web Conf.

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Ontologies are the main tool for representing domain knowledge. The need to use ontologies to ensure consistent behavior of autonomous intelligent systems in agriculture is determined by the need to create semantic interactiveness of agricultural systems and decision support systems, in which automatic knowledge inference occurs based on semantic processing of data from a sensor network. The purpose of the study is to develop methods for constructing ontologies to ensure consistent behavior of autonomous intelligent systems in agriculture. The paper presents the architecture of an intelligent control system for a heterogeneous human-machine team, consisting of an autonomous robot for active plant protection and an unmanned aerial vehicle (UAV) for monitoring the condition of the garden from the air. A multiagent architecture for constructing ontologies has been developed to ensure consistent behavior of a human-machine team. In particular, a multiagent architecture for constructing an ontology when a robot detects a new object is presented, as well as a scheme for exchanging knowledge between team members. The results obtained can be used in the development of decision support systems, in which automatic knowledge inference occurs based on semantic processing of data from a sensor network.

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Review on the Work of Agriculture Ontology Research Group

Cited by 3 publications

References 4 publications

A Framework for Evaluating Agricultural Ontologies

A Framework for Evaluating Agricultural Ontologies

An Exploratory Study on Agriculture Ontology: A Global Perspective

Methods for building ontologies to ensure coordinated behavior of autonomous intellectual systems in agriculture

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