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Development of RESTful Web Service for Loading Data focusing on Daily Meteorological Data

데이터 로딩 자동화를 위한 RESTful 웹서비스 개발 - 일별 기상자료 처리를 중심으로 -

  • Kim, Taegon (Institute of Green Bio Science and Technology, Seoul National University) ;
  • Lee, JeongJae (Department of Landscape Architecture and Rural Systems Engineering, Research Institute of Agriculture and Life Sciences, Seoul National University) ;
  • Nam, Won-Ho (School of Natural Resources, University of Nebraska-Lincoln) ;
  • Suh, Kyo (Graduate School of International Agricultural Technology, Institute of Green Bio Science and Technology, Seoul National University)
  • Received : 2014.08.11
  • Accepted : 2014.11.12
  • Published : 2014.11.30

Abstract

Generally data loading is a laborous job to develop models. Meteorological data is basic input data for hydrological models, it is provided through websites of Korea Meteorological Administration (KMA). The website of KMA provides daily meteorological observation data with tabular format classified by years, items, stations. It is cumbersome to manipulate tabular format for model inputs such as time series and multi-item or multi-station data. The provider oriented services which broadcast restricted formed information have caused inconvenient processes. Tim O'Reilly introduces "Web 2.0" which focuses on providing a service based on data. The top ranked IT companies such as google, yahoo, daum, and naver provide customer oriented services with Open API (Application Programming Interface). A RESTful web service, typical implementation for Open API, consists URI request and HTTP response which are simple and light weight protocol than SOAP (Simple Object Access Protocol). The aim of this study is to develop a web-based service that helps loading data for human use instead of machine use. In this study, the developed RESTful web service provides Open API for manipulating meteorological data. The proposed Open API can easily access from spreadsheet programs, web browsers, and various programming environments.

Keywords

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