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A tool to dynamically merge corresponding weather data to crop data Xinwen Yu, Seishi Ninomiya, Atsushi Yamakawa National Agriculture Research Center,

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Presentation on theme: "A tool to dynamically merge corresponding weather data to crop data Xinwen Yu, Seishi Ninomiya, Atsushi Yamakawa National Agriculture Research Center,"— Presentation transcript:

1 A tool to dynamically merge corresponding weather data to crop data Xinwen Yu, Seishi Ninomiya, Atsushi Yamakawa National Agriculture Research Center, Tsukuba, Japan

2 Dead Storage Data Issue A lot of digital data sets are continuously produced in agricultural experimental stations Using ordinal software such as spread sheet applications But they are likely to be kept in local stations and scientist level The data sets are isolated and hardly integrated among different locations How to ease data publication for merging and sharing for end users

3 Different resource integration issue Separated crop data are hard to be integrated with different resources, e.g. weather data Heterogeneity e.g. Models constructed using local data are only applicable locally How to integrate crop data with weather data under user ’ s request

4 If merging and sharing are possible, End users can freely combine separated data sets from different locations and perform analysis on them Datamining over the huge amount of data sets becomes real and we can possibly find out unknown facts Integration with completely different resources e.g. weather data becomes also possible Constructing global model also becomes possible

5 With Web-based data sharing & integration Once you upload experimental data in spreadsheet file (e.g. MS Excel), data automatically become sharable over the Internet among different locations Crop data can be integrated with weather data No skill is required Just a part of everyday data management Uniformity of tables is not required Low cost

6 Internet DBMS Application Server Servlet Container EJB Container Application Concept Multi-location data sharing and integration Integration with weather data MetBroker

7 Basic structure of application Google Map Client Browser Controller Crop DB Crop Data Service Model Services Web application MetBroker AMeDAS View

8 System components Java Runtime Environment 1.5.04 PostgreSQL7.4 JRE supported OS JBoss-4.0.3 EJB3.0 (DBMS abstraction) Struts1.2 (Web Interface) ・ IE, Firefox, etc. ・ Excel2002, newer

9 Main menu Very simple menu structure Simple and clean user interface

10 Data upload Crop Data Service EJB3 SourceX ML CropData History Data transforming Data validating XSLT style sheet Data Schema a b c Crop Database a.Transformation of source data file using style XSLT style sheet, storing source data file in XML to SourceXML table. b.Validating transformed data XML using data schema c.Data service binds data XML to data object (JAXB), maps data object to data records to CropData table; stores uploaded information including user name, spreadsheet file name, uploading time, count of data record to History table.

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12 Upload history

13 Web Application Crop Data Service EJB3 Crop db Specifying query conditions then executing data query. Browsing and/or download queried crop data Data Query

14 AMeDAS Web Application Crop Data Location Table Crop Data Service EJB3 MetBroker a b AMeDAS c d Data integration

15 Location registration

16 Weather station selection

17 Discussion 37 spreadsheet files uploaded 151072 records 6486 varieties 184 properties 256 different experiment locations 1980-2004 Available to open society

18 Data integration is realized in our brokerage based Data Grid MetBroker is the core of the Data Grid The application demonstrates the power of Data Grid This approach can be used to all other crop data sharing and integration Crop modelers are using this application to develop robust crop models

19 Thank you for your attention


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