A Framework for Evaluating Agricultural Ontologies

Abstract

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.

An ontological model to support citizen science in the field of invasive species research

“…In the formalized description of knowledge regarding the IAS citizen sciences, through the use of ontologies it is necessary to take into account the possibility of including an explicit evaluation procedure, as without a well-structured one it will be difficult to assess the suitability of developed models in related research and their practical application [12]. Ontologies provide the necessary basis for the proper operation of semantic network-based applications -technologies that can provide instructions and clear rules in the processes of data collection, integration and use [13] in IAS citizen sciences initiatives. By providing semantic interoperability of the descriptive models built for presenting the information, the use of ontologies will allow for the generation and analysis of different scenarios in their implementation [14], with the help of built-in visualization tools showing the connection and interaction between the individual classes, as well as the flow of information and the specific properties of the objects within the classes.…”

Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application

“…Recent ontologies proposed in the research literature are [1,2,[8][9][10]. A short description of these contributions is as follows.…”

“…It has four areas: geographical ontology, business sub-domain, IoT-based sub-domain, and agriculture-based sub-domain. In [9], authors proposed a framework that matches evaluation approaches that are gold-standard, application-based, criteria-based, and data-driven to different ontology purposes that share vocabularies and integrate data, system interoperability, knowledge search and exploration, and decision support. In [10], the authors developed SAAONT, which is specifically focused on the farmers of the Saudi Arabia region.…”

“…In [8], the author proposed a framework, but that framework has the limitation of context-awareness, scalability, and service-oriented architecture. In [9], the authors only work on pest-ontology and apply evaluation methods discussed above. In future research, it can be implemented on other agriculture ontologies.…”

“…Many researchers utilized Protégé in their works [1,9,24]. This work implements both ONTAgri and ONTAgriX ontologies in Protégé for precision farming applications.…”