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A frame work for virtual integration of distributed heterogeneous data of breeding/crop experiments by Data Grid technology

基于数据网格技术的育种/作物实验分布式异构数据虚拟集成框架

基本信息

批准号：
16380011
负责人：
NINOMIYA Seishi
金额：
$ 8.7万
依托单位：
National Agriculture and Food Research Organization
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2006
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-16380011/
关键词：
data grid breeding information crop information information sharing data mining

项目摘要

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.

通过育种和作物实验积累了大量的数据集。不同实验站的数据集异构且分散，很少合并用于整体研究，导致有价值数据的死存储。本研究的目的是开发一个框架，为我们提供一个虚拟集成这种分布式异构数据集的环境，从而实现对完全合并的数据集的分析。 1．用于合并分布式和异构数据集的作物数据库：通过分析在多个地点通过育种和作物实验记录的几种类型的数据集，我们定义了标准作物数据格式。用户上传的数据集会根据吸收异质性的样式表定义自动转换为标准格式，以便统一存储在作物数据库中。用户可以简单地将本地定义的序数数据集上传到数据库，并轻松合并来自不同位置的数据集。2．农作物数据和气象数据的集成：利用MetBroker可以为我们提供对分布式异构天气数据库的一致访问，开发了一种半自动集成农作物数据与位置和周期性相应天气数据的系统。 3．该框架使用从多个农业试验站收集的超过 150,000 条水稻数据记录进行了测试。4．提供日语和英语的用户手册。5。该框架使得对广泛合并的数据集进行作物建模和数据挖掘成为可能，整合分布式作物数据集和相应的天气数据，这在以前是不容易实现的。