论文标题
数据科学：挑战和方向
Data Science: Challenges and Directions
论文作者
论文摘要
尽管数据科学已成为一个有争议的新科学领域，但已经对此进行了巨大的辩论和讨论，为什么我们需要数据科学及其成为科学的原因。在审查包括数据科学在内的数百种文学作品时，我们发现大多数讨论基本上涉及统计数据，数据挖掘，机器学习，大数据或广泛的数据分析，并且仅探索了有限的新数据驱动挑战和方向。在本文中，我们探讨了通过全面探索数据科学问题中嵌入的复杂性和智能启发的内在挑战和方向。我们专注于受数据科学问题作为复杂系统的性质以及处理此类系统的方法的启发的研究和创新挑战。
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.
