Digital Knowledge Ecosystem for Achieving Sustainable Agriculture Production: A Case Study from Sri Lanka
Crop production problems are common in Sri Lanka which severely effect rural farmers, agriculture sector and the country's economy as a whole. A deeper analysis revealed that the root cause was farmers and other stakeholders in the domain not receiving right information at the right time in the right format. Inspired by the rapid growth of mobile phone usage among farmers a mobile based solution is sought to overcome this information gap. Farmers needed published information (quasi static) about crops, pests, diseases, land preparation, growing and harvesting methods and real time situational information (dynamic) such as current crop production and market prices. This situational information is also needed by agriculture department, agro chemical companies, buyers and various government agencies to ensure food security through effective supply chain planning whilst minimising waste. We developed a notion of context specific actionable information which enables user to act with least amount of further processing. User centered agriculture ontology was developed to convert published quasi static information to actionable information. We adopted empowerment theory to create empowerment oriented farming processes to motivate farmers to act on this information and aggregated the transaction data to generate situational information. This created a holistic information flow model for agriculture domain similar to energy flow in biological ecosystems. Consequently, the initial Mobile based Information System evolved into a Digital Knowledge Ecosystem that can predict current production situation in near real enabling government agencies to dynamically adjust the incentives offered to farmers for growing different types of crops to achieve sustainable agriculture production through crop diversification.
2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA)