Ontology based knowledge representation: Case study from agriculture domain

Abstract

The growth of web has touched everyone’s life from an economist, entrepreneur, and academician to a farmer. The agriculture sector is quite important for any country’s growth. Farmers can also be benefited if they are provided with relevant information they need. The reason that it is not happening on a large scale is due to many reasons. Information is available in different formats, platforms and it is highly unstructured. The availability and real time usage of this information is prohibited mainly by the way it is represented. Recently, Ontology has emerged as one of very expressive knowledge representation scheme which enables gathering information from heterogeneous sources and creates a common data model that is shared and agreed upon in diverse domains. The interoperability and deduction capabilities that Ontology offers are very useful for generating new knowledge. Most of the work pertaining to ontology development in agriculture domain is crop specific, where information about fertilizers is confined to a particular crop only. In this paper, we have designed and developed a generic ontology for fertilizers. Fertilizer itself is a concept which should be modeled independently. Even for crop specific ontology, fertilizer is one of the most important concept to be captured. So, it needs to be represented independently. Finding this research gap, an ontology in fertilizer subdomain is developed, taking into account the various issues that are faced while constructing an ontology and the enormous amount of data that is available but is not easy to structure and present in the form of ontology. We have also validated the Ontology using an available tool and domain experts have also validated the developed Ontology.

OntoCSA

“…Other modules of the AgriOnt are extended with more sub classes to represent complete IoT-based agriculture systems. The concepts of AgOnt (Hu et al, 2011) and AgriOnt (Ngo et al, 2018) ontologies provide an extensive overview of agricultural farming; however, their design did not include any concepts on climate change in agriculture.…”

“…To the authors knowledge, this is the first report to develop an ontology of CSA. The OntoCSA ontology proposed, in this study, can be integrated with existing agriculture ontologies (Hu et al, 2011;Dineshkumar et al, 2014;Ngo et al, 2018), to build current ontologies for the agriculture domain, that include todays realities of climate change in agriculture. The methodology used in this study is presented and applied in the next section.…”

“…The vocabulary of the CSA domain was constructed by reading related literature on CSA from websites ("Climate-Smart Agriculture", n.d.; Papuso & Faraby, 2013;FAO, 2017), published research articles and reports (Smith & Gregory, 2012;Lipper et al, 2014;Amin et al, 2015;FISH, 2016;FAO, 2018a;Raza et al, 2019) and analyzing existing related agricultural ontologies (Hu et al, 2011;Kim et al, 2013;Dineshkumar et al, 2014;Harika & Bhargav, 2015;Sivamani et al, 2016;Ngo et al, 2018). Furthermore, lists of competency questions (CQs) and role players involved in CSA were drawn to delimit the scope of the target OntoCSA ontology.…”

“…An ontology represents a knowledge domain formally, through its entities, concepts, objects and the relationships between them (Busse et al, 2015). Ontology represents common and shared terminologies of a domain (Nidhi et al, 2021) in both conceptual and machine-readable forms, and, thereby, provides a shared comprehension of the representation of information to the community of peoples as well as enables automated processing of knowledge in the domain. Ontology enables the integration of subsystems of a domain and facilitates their interoperability (Taye, 2010;Roussey et al, 2010;Goldstein et al, 2019;Nidhi et al, 2021)).…”

“…Ontology represents common and shared terminologies of a domain (Nidhi et al, 2021) in both conceptual and machine-readable forms, and, thereby, provides a shared comprehension of the representation of information to the community of peoples as well as enables automated processing of knowledge in the domain. Ontology enables the integration of subsystems of a domain and facilitates their interoperability (Taye, 2010;Roussey et al, 2010;Goldstein et al, 2019;Nidhi et al, 2021)). In fact, the subsystems of a domain that use the same ontology process the same terminologies, which may facilitate their integration and interoperability.…”