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Construction of Integrated Agricultural Statistical System Architecture for Effective Policy  

Lee, Min-Soo (Dept. of Agricultural Economics and Rural Development, Seoul Notional University)
Chae, Young-Chan (Dept. of Agricultural Economics and Rural Development, Seoul Notional University)
Hong, Hee-Yeon (Dept. of Agricultural Economics and Rural Development, Seoul Notional University)
Kim, Sang-Ho (Dept. of Agricultural Economics and Rural Development, Seoul Notional University)
Kim, Jeong-Seop (Dept. of Agricultural Economics and Rural Development, Seoul Notional University)
Publication Information
Journal of Korean Society of Rural Planning / v.11, no.4, 2005 , pp. 75-91 More about this Journal
Abstract
This study designs an integrated data architecture to systematically manage the agricultural statistics database. Managing the agricultural statistics is important since it provides data for policies and decision making for agribusinesses. Ministry of Agriculture and the National Statistical Office collect the basic agricultural statistic data which provides the basis of logical decision making and agricultural policies. However, the agricultural statistic data has not well been used. The data has not been consistently collected nor managed. The raw data has not been organized nor processed to meet various demands. The needs has been arisen for a consistent agricultural statistics system to increase the relevance, accessibility, and efficiency of data for various users. There are massive amount of data accumulated over a long time period. Introducing the new system and reorganizing the data will bear large risks. A systematic method is required to reduce the risks in planing, building, and maintaining the database without hindering administration. This study provides a design of the agricultural statistics system architecture based on the user requirement analysis (URA) and similar systems abroad. We have also build a prototype to check the implementability of the system design.
Keywords
Agricultural statistics; Data warehouse; ETL(Extraction, Transformation, Loading) tool;
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