Multi-Scale Data Integration Challenges in the Observational Science Data Space

被引:0
|
作者
Berti-Equille, Laure [1 ]
机构
[1] Inst Rech Dev, Aix En Provence, France
来源
IT-INFORMATION TECHNOLOGY | 2012年 / 54卷 / 03期
关键词
Information Systems: Database Management: Database Applications; scientific databases; new trends in data integration; geoscience data; multi-scale data integration; spatio-temporal data;
D O I
10.1524/itit.2012.0672
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In Europe, more than one thousand of laboratories intensively collect data to measure various properties of the Earth. Scientists observe environmental conditions, ecosystems and biological species. The ability to understand complex phenomena (e.g., global warming) and predict trends from spatio-temporal data becomes a major issue in observational science. However, theoretical and technical advances in multi-scale data integration are necessary to achieve this. This paper will present some challenging research directions for integrating such massive multi-scale scientific data.
引用
收藏
页码:123 / 128
页数:6
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