Real Time Semantic Search for Agriculture using Ontology and RDF Repository.

Knowledge has the potential to become data in a sense that it can be used for deriving new ideas, relating new disciplines and more importantly expressing facts in ways that have only been possible through publication of documents. Using methods for quantifying knowledge about agriculture, the underutilized crop filed knowledge-based system will make the promotion and research on these neglected crops for food and non-food purposes more widespread. The knowledge database will store facts of interest about unknown crops from the peer reviewed and verified sources. The database design will follow standard vocabularies and ontologies that are developed through years by the agricultural community. These standard ontologies will provide ground for the development of semantic products like 'query system' and 'answer engines' that can provide direct answers to direct questions. The actual information will also be linked to real experimental data created by research groups through the other component, This paper provides solutions to various problems related to weather based Agricultural Census data in these aspects: (1) Storage/Organization of census data using enhanced methods such as ontologies. In this context standard vocabularies and ontology languages will be used for metadata storage and retrieval as well as relating research data to knowledge. By applying NPK values to visualize the clear details from mobile app to the farmers.