1. Development of Data Science：the Advantages and Challenges of iSchool
Zhou Xiaoying , Feng Xiangmei
School of Information Resources Management,
Renmin University of China

2. We discussed these：
Data science is an interdisciplinary research field，iSchools members have a strong interdisciplinary structure
Coverage of Disciplines
One of the tasks of data science is to solve the problems of obtaining knowledge from data，the “data - information - knowledge - wisdom” theory has been generally accepted in information science for long time.
"Data - Information - Knowledge" Chain
Three aspects
How many libraries in the world? Do they have close cooperation? They can do in data literacy promotion like they’ve done in information literacy promotion.
International Cooperation in Data Literacy Promotion

3. Advantages and Challenges1——Coverage of Disciplines
Advantage: the domain iSchool members contains is quite interdisciplinary (member contain computer science, communication science, humanities and social sciences, library and information science) , So iSchool on data science research has unique conditions.
Challenge: to integrate interdisciplinary research efforts, and to achieve the leading position in the data science at the combination point of data-technology-human interface.

4. Advantages and Challenges2 ——"Data - Information - Knowledge" Chain
Advantage: “data-information-knowledge-wisdom” chain has always been research topic and teaching courses on library and information science of the iSchool members, the accumulation of theory and practice will continue to be applied and promoted in the development of data science
Challenge: there are a number of participants in the development of data science, and LIS disciplines need to deepen and expand traditional knowledge from data integration and understanding to data perceptions and interactions, and then, to data learning and cognition.

5. Advantages and Challenges3 ——International Cooperation in Data Literacy Promotion
Advantage: iShool can make use of the accumulated experience and international cooperation model of information literacy education, carry out global data literacy education, enhance the society's awareness and perception of data as a whole, and can also make global collaboration in many aspects
Challenge: how to differentiate between information literacy and data literacy, how to develop a reasonable standard for data literacy, and how to develop a global data literacy education for different data needs and applications.

6. We should consider：
In data science，What problems need to be solved by us？
In data science，What is our unique contribution？ ？

7. Thank You !