  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.
