While data science has emerged as a contentious new scientific field, enormous debates and discussions have been made on it why we need data science and what makes it as a science. In reviewing hundreds of pieces of literature which include data science in their titles, we find that the majority of the discussions essentially concern statistics, data mining, machine learning, big data, or broadly data analytics, and only a limited number of new data-driven challenges and directions have been explored. In this paper, we explore the intrinsic challenges and directions inspired by comprehensively exploring the complexities and intelligence embedded in data science problems. We focus on the research and innovation challenges inspired by the nature of data science problems as complex systems, and the methodologies for handling such systems.

中文翻译：

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数据科学：挑战和方向

虽然数据科学已经成为一个有争议的新科学领域，但关于为什么我们需要数据科学以及是什么使它成为一门科学，已经进行了大量的辩论和讨论。在回顾数百篇标题中包含数据科学的文献时，我们发现大多数讨论主要涉及统计、数据挖掘、机器学习、大数据或广泛的数据分析，只有有限数量的新数据——已经探索了驱动的挑战和方向。在本文中，我们通过全面探索数据科学问题中的复杂性和智能性来探索内在挑战和方向。我们专注于受数据科学问题作为复杂系统的性质启发的研究和创新挑战，以及处理此类系统的方法。