Authors:
Anusha Indika Walisadeera
1
;
Gihan Nilendra Wikramanayake
2
and
Athula Ginige
3
Affiliations:
1
University of Western Sydney and University of Colombo, Australia
;
2
University of Colombo, Sri Lanka
;
3
University of Western Sydney, Australia
Keyword(s):
Agricultural Knowledge, Social Life Network, Knowledge Representation, Ontology, Ontology Design.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Retrieval
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Management
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Pattern Recognition
;
Society, e-Business and e-Government
;
Software Engineering
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
Rapid adoption of mobile phones has vastly improved access to information. Yet finding the information within the context in which information is required in a timely manner is a challenge. To investigate some of the underlying farmer centric research challenges a large International Collaborative Research Project to develop mobile based information systems for people in developing countries has been launched. One major sub project is to develop a Social Life Network; a mobile based information system for farmers in Sri Lanka. Lack of timely information with respect to their preferences and needs to support farming activities is creating many problems for farmers in Sri Lanka. For instance, farmers need agricultural information within the context of location of their farm land, their economic condition, their interest and beliefs, and available agricultural equipment. As a part of this project we investigated how we can create a knowledge repository of agricultural information to res
pond to user queries taking into account the context in which the information is needed. Because of the complex nature of the relationships among various concepts we selected an ontological approach that supports first order logic to create the knowledge repository. We first identified set of questions that reflect various motivation scenarios. Next we created a model to represent user context. Then we developed a novel approach to derive the competency questions incorporating user context. These competency questions were used to identify the concepts, relationships and axioms to develop the ontology. Initial system was trialled with a group of farmers in Sri Lanka. There was universal agreement among the farmers participated in the field trial to varying degree (strongly agree, agree, moderately agree) to the question “All information for the crop selection stage is provided”.
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