| Project/Area Number |
16380011
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Breeding science
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| Research Institution | National Agriculture and Food Research Organization |
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Principal Investigator |
NINOMIYA Seishi National Agriculture and Food Research Organization, National Agricultural Research Center, Research Manager, 中央農業総合研究センター, 研究管理監 (90355488)
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| Co-Investigator(Kenkyū-buntansha) |
IWATA Hiroyoshi National Agriculture and Food Research Organization, National Agricultural Research Center, Senior Scientist, 中央農業総合研究センター・データマイニング研究チーム, 主任研究員 (00355489)
HORYU Daisuke National Agriculture and Food Research Organization, National Agricultural Research Center, Senior Scientist, 中央農業総合研究センター・データマイニング研究チーム, 主任研究員 (70355486)
WATANABE Tomoya National Agriculture and Food Research Organization, National Agricultural Research Center, Team Leader, 中央農業総合研究センター・班点米カメムシ研究チーム, チーム長 (20355548)
SHIMADA Shinji National Agriculture and Food Research Organization, National Agricultural Research Center, Team Leader, 中央農業総合研究センター・大豆生産安定研究チーム, チーム長 (30355309)
HASEGAWA Toshihiro National Agriculture and Food Research Organization, National Agricultural Research Center, Senior Scientist, 大気環境研究領域, 主任研究員 (10228455)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥13,600,000 (Direct Cost: ¥13,600,000)
Fiscal Year 2006: ¥3,000,000 (Direct Cost: ¥3,000,000)
Fiscal Year 2005: ¥7,300,000 (Direct Cost: ¥7,300,000)
Fiscal Year 2004: ¥3,300,000 (Direct Cost: ¥3,300,000)
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| Keywords | data grid / breeding information / crop information / information sharing / data mining |
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| Research Abstract |
Huge amount of data sets have been being accumulated through breeding and crop experiments. The data sets are heterogeneous and separated among different experimental stations and are rarely merged for total researches, causing dead storage of valuable data. This study was conducted to develop a frame work that can provide us an environment to virtually integrate such distributed heterogeneous data sets so as to realize analyses on totally merged data sets.
1. Crop database to merge distributed and heterogeneous data sets : Analyzing several types of data sets recorded through breeding and crop experiments in several locations, we defined standard crop data format. Uploaded data sets from users are automatically transformed to the standard format based on style sheet definitions that absorbs heterogeneity so that these are stored in the crop database uniformly. Users can simply upload their ordinal data sets that are locally defined to the database and easily merge data sets from different locations.
2. Integration of crop data and meteorological data : Utilizing MetBroker that can provide us consistent access to distributed and heterogeneous weather databases, a system to semi-automatically integrate crop data with positionally and periodically corresponding weather data was developed.
3. The frame work was tested using more than 150,000 records of rice data collected from several agricultural experimental stations.
4. User manuals in both Japanese and English were provided.
5. The frame work makes it possible to conduct crop modeling and datamining of widely merged data sets, integrating distributed crop data sets and corresponding weather data, which was not easily realized before.
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