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Editorial 2020 Part II: Data from nowhere?

机译:2012年2020年第二部分:来自无处的数据?

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摘要

This short editorial reflects upon and explains ESPL's policy with respect to data sharing. Whilst there are clearly a number of important reasons why data should be shared, notably to support transparency in science and to support the long-term monitoring of geomorphological change, data sharing comes with some concerns. Data sharing cannot become an alternative to field data collection as it produces a scientific understanding of a very particular type. When shared data are combined in extensive analyses we run the serious risks of inter-comparability, bias and incompleteness. Automated harnessing and analysis of any kind of geomorphological data runs the risk of combining data that are not comparable and producing conclusions skewed to the datasets available. Shared data allow for none of the serendipity that comes from being in the field and being confronted by what we see and experience; they might as well be data from nowhere. We must be particularly careful not to reduce the perceived value of field data collection in an academic system that places ever more emphasis on speed and efficiency in scientific knowledge production. It is for these reasons that ESPL's policy on data sharing is to support it and to encourage it, notably through requiring authors to provide a data statement, but we will not insist that data should be published as a condition of manuscript acceptance. (c) 2019 John Wiley & Sons, Ltd.
机译:这简短的社论反映并解释了ESPL关于数据共享的政策。虽然有一些重要的原因,但要分享数据的重要原因,特别是支持科学透明度并支持长期监测地貌变化,数据共享带来了一些问题。数据共享不能成为现场数据收集的替代品,因为它产生了对非常特殊类型的科学了解。当共享数据在广泛的分析中组合时,我们运行了可比性间,偏见和不完整性的严重风险。任何类型的地貌数据的自动化利用和分析运行了与可用的数据集倾斜的数据组合并产生结论的风险。共享数据允许避免在现场中的诸如诸如我们所看到和经验的人;它们也可能是无处可去的数据。我们必须特别小心,不要减少学术系统中现场数据收集的感知价值,以更加重视科学知识生产的速度和效率。由于这些原因,ESPL关于数据共享的政策是支持它并鼓励它,特别是通过要求作者提供数据声明,但我们不会坚持应作为稿件接受的条件发布。 (c)2019 John Wiley&Sons,Ltd。

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