Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributes in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. With these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.

中文翻译：

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高通量X射线衍射测量的实时数据评估。

对更明亮的光源和更大，更快的检测器的投资加快了国家用户设施中数据采集的速度。加速的数据采集为发现新材料提供了许多机会，但同时也带来了艰巨的挑战。数据采集​​的速度远远超过了当前的数据质量评估速度，导致数据和覆盖范围不足，这在极端情况下会迫使数据重新收集。本文中，我们展示了如何通过开发一种使常规数据评估自动且即时的方法来应对这一挑战。通过实时提取和可视化自定义属性，可以突出显示数据质量和覆盖范围以及大数据集中包含的其他与科学相关的信息。部署这种方法不仅可以提高数据质量，还可以通过优先考虑对最高科学影响的测量来帮助优化昂贵的表征资源的使用。我们预计我们的方法将成为复杂决策树的起点，该决策树可通过自动化实时优化数据质量并最大化科学含量。通过这些努力将更多的自动化集成到数据收集和分析中，我们可以真正利用加速的数据采集速度。我们预计我们的方法将成为复杂决策树的起点，该决策树可通过自动化实时优化数据质量并最大化科学含量。通过这些努力将更多的自动化集成到数据收集和分析中，我们可以真正利用加速的数据采集速度。我们预计我们的方法将成为复杂决策树的起点，该决策树可通过自动化实时优化数据质量并最大化科学含量。通过这些努力将更多的自动化集成到数据收集和分析中，我们可以真正利用加速的数据采集速度。