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Applying big data beyond small problems in climate research

机译:应用大数据超出气候的小问题研究

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摘要

Commercial success of big data has led to speculation that big-data-like reasoning could partly replace theory-based approaches in science. Big data typically has been applied to 'small problems', which are well-structured cases characterized by repeated evaluation of predictions. Here, we show that in climate research, intermediate categories exist between classical domain science and big data, and that big-data elements have also been applied without the possibility of repeated evaluation. Big-dataelements can be useful for climate research beyond small problems if combined with more traditional approaches based on domain-specific knowledge. The biggest potential for big-data elements, we argue, lies in socioeconomic climate research.
机译:大数据导致的商业上的成功猜测big-data-like推理部分替代基于理论的方法科学。“小问题”,这是结构良好的用例特点是重复评价预测。研究,中间类别之间存在古典科学大数据领域,大数据元素也被应用重复的可能性的评估。Big-dataelements气候是非常有用的如果结合研究之外的小问题基于更传统的方法特定领域的知识。对于大数据元素,我们认为,谎言社会经济气候研究。

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