User centered ontology for Sri Lankan farmers

Farmers in Sri Lanka are badly affected by not being able to get vital information required to support their farming activities in a timely manner. Some of the required information can be found in government websites, agriculture department leaflets, and through radio and television programs on agriculture. This knowledge is not reaching the farmers due to its unstructured, incomplete, varied formats, and lack of targeted delivery methods. Thus finding the right information within the context in which information is required in a timely manner is a challenge. The information and knowledge needs to be provided not only in a structured and complete way, but also in a context-specific manner. 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. To investigate some of the underlying farmer centric research challenges an International Collaborative Research Project to develop mobile based information systems for people in developing countries has been launched. Farmer centered ontology was developed as part of this project. Agricultural information has strong local characteristics in relation to climate, culture, history, languages, and local plant varieties. These local characteristics as well as the need to provide information in a context-specific manner made us develop this user centered ontology for Sri Lankan farmers. Because of the complex nature of the relationships among various concepts we selected an ontological approach that supports description logic to create the knowledge repository. For this we developed a new approach to model the domain knowledge to meet particular access requirements of the farmers in Sri Lanka. Through this approach, we have investigated how to create a knowledge repository of agricultural information to respond to user queries taking into account the context in which information is needed by farmers at various stages of the farming life cycle. The Delphi Method and the OOPS! (web-based tool) were used to validate the ontology. Initial system was trialed with a group of farmers in Sri Lanka. The online knowledge base with a SPARQL endpoint was created to share and reuse the domain knowledge that can be queried based on farmer context.