有效科学的七项原则Big-DataSystems
Seven Principles for Effective Scientific Big-DataSystems
摘要：
我们应该处于科学发现的黄金时代，因为我们比以往任何时候都拥有更多的数据和更强大的计算能力，再加上新一代的算法可以有效地从数据中学习。但矛盾的是，在许多数据驱动的领域，“尤里卡时刻”正变得越来越罕见。科学家们正在努力跟上科学数据数量和复杂性爆炸的步伐。我们在这里描述了一些简单的架构原则，我们认为这些原则对于创建有效、健壮和灵活的平台至关重要，这些平台可以最好地利用新兴技术来处理科学数据的指数增长。
英文摘要：
We should be in a golden age of scientific discovery, given that we have more data and more compute power available than ever before, plus a new generation of algorithms that can learn effectively from data. But paradoxically, in many data-driven fields, the eureka moments are becoming increasingly rare. Scientists are struggling to keep pace with the explosion in the volume and complexity of scientific data. We describe here a few simple architectural principles that we believe are essential in order to create effective, robust, and flexible platforms that make the best use of emerging technology to deal with the exponential growth of scientific data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
