School of Information Management Nanjing University China Unique Contributions and Opportunities of iSchools in Data Science Education Han Xi Zhu Qinghua School of Information Management Nanjing University China

Definition of Data Science the study of the extraction of knowledge from data concerned with the collection, preparation, analysis, visualization, management, and preservation of large collections of information involves principles, processes, and techniques for understanding phenomena via the analysis of data employs techniques and theories drawn from different fields within the broad areas of mathematics, statistics and information technology

Definition of Data Scientist have to master the knowledge and the skills of data mining, statistics, information technology, information visualization and communication, as well as engineering and computer science. They also should acquire experiences in the specific research or industry domain of their future work and specialization. need to integrate structured and unstructured data sources, apply analytics beyond traditional data processing (data mining, machine learning, and artificial neural networks), and communicate the analysis to audience

Four Contributions and Opportunities 1 Data Thinking Data Management 2 Absorptive Capacity of Information Technology 3 Interdisciplinary Attributes 4

Data Thinking Data thinking is the generic mental pattern observed during the processes of picking a subject to start with, identifying its parts or components, organizing and describing them in an informative fashion that is relevant to what motivated and initiated the whole processes. Data thinking is even more vital，just like culture

Data Management From a more macroscopic perspective, the activity throughout data life-cycle is data management, including data collection, preservation, organization, analysis and the dissemination of results for data-based decision making.

Absorptive Capacity of Information Technology information science cannot surpass the computer science on information technology frontier research and development, it is effective in absorbing information technology and applying it into daily practice. there are no other disciplines that pay more attention to the application of information technology to solve problem than information science.

Interdisciplinary Attributes Data science requires not only information technology, data management capabilities and statistical methods, but also inter-disciplinary knowledge to solve various questions in different backgrounds. It is a broad and interdisciplinary field

What should we do? The reform of information science education towards data science education is necessary and urgent. We need to introduce more topics such as machine learning, programming, predictive modeling and statistics methods and tools that are currently closely associated with data science. We should focus on data analytics and conduct different kinds of programs to train specialists

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