Knowledge Engineering for Apportioning District Level Data in Agriculture

Abstract

Agriculture is the backbone of India and data is a driver of growth and change. In agriculture domain also, large amount of data is being collected by various agencies including Government of India. The data is generated every day at various levels namely household, village, district, state and country. Data collection is done and recorded at current status regarding spatial boundaries of the units. At country level, there is no change in the boundary. State level spatial changes are rare and easy to capture in the data analysis. But, district level temporal data analysis creates problem because of the variation in number of districts and changes in their areas over a period of time. Thus, temporal data at district level requires adjustment called apportioning before analysis. These adjustment in data vary from variable to variable. The paper discusses apportioning methodology for different categories of variables using mathematical notations as well as using software named DAS developed for this purpose. The software has been developed using the programming language C# and tested using different datasets. The software called DAS (http://das.iasri.res.in) has been developed and also made available online.