<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Due to the recent explosion of big data, our society has been rapidly going through digital transformation and entering a new world with numerous eye-opening developments. These new trends impact the society and future jobs, and thus student careers. At the heart of this digital transformation is data science, the discipline that makes sense of big data. With many rapidly emerging digital challenges ahead of us, this article discusses perspectives on iSchools’ opportunities and suggestions in data science education. We argue that iSchools should empower their students with “information computing” disciplines, which we define as the ability to solve problems and create values, information, and knowledge using tools in application domains. As specific approaches to enforcing information computing disciplines in data science education, we suggest the three foci of user-based, tool-based, and application-based. These three foci will serve to differentiate the data science education of iSchools from that of computer science or business schools. We present a layered Data Science Education Framework (DSEF) with building blocks that include the three pillars of data science (people, technology, and data), computational thinking, data-driven paradigms, and data science lifecycles. Data science courses built on the top of this framework should thus be executed with user-based, tool-based, and application-based approaches. This framework will help our students think about data science problems from the big picture perspective and foster appropriate problem-solving skills in conjunction with broad perspectives of data science lifecycles. We hope the DSEF discussed in this article will help fellow iSchools in their design of new data science curricula.</p></abstract>

Due to the recent explosion of big data, our society has been rapidly going through digital transformation and entering a new world with numerous eye-opening developments. These new trends impact the society and future jobs, and thus student careers. At the heart of this digital transformation is data science, the discipline that makes sense of big data. With many rapidly emerging digital challenges ahead of us, this article discusses perspectives on iSchools’ opportunities and suggestions in data science education. We argue that iSchools should empower their students with “information computing” disciplines, which we define as the ability to solve problems and create values, information, and knowledge using tools in application domains. As specific approaches to enforcing information computing disciplines in data science education, we suggest the three foci of user-based, tool-based, and application-based. These three foci will serve to differentiate the data science education of iSchools from that of computer science or business schools. We present a layered Data Science Education Framework (DSEF) with building blocks that include the three pillars of data science (people, technology, and data), computational thinking, data-driven paradigms, and data science lifecycles. Data science courses built on the top of this framework should thus be executed with user-based, tool-based, and application-based approaches. This framework will help our students think about data science problems from the big picture perspective and foster appropriate problem-solving skills in conjunction with broad perspectives of data science lifecycles. We hope the DSEF discussed in this article will help fellow iSchools in their design of new data science curricula.

Big Data and Data Science: Opportunities and Challenges of iSchools

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Big Data and Data Science: Opportunities and Challenges of iSchools"}

Due to the recent explosion of big data, our society has been rapidly going through digital transformation and entering a new world with numerous eye-opening...

Big Data and Data Science: Opportunities and Challenges of iSchools

Article Category: Perspective

Online veröffentlicht: 22. Aug. 2017

Seitenbereich: 1 - 18

Eingereicht: 25. März 2017

Akzeptiert: 18. Apr. 2017

DOI: https://doi.org/10.1515/jdis-2017-0011

Schlüsselwörter
Big data, Data science, Information computing, The fourth Industrial Revolution, iSchool, Computational thinking, Data-driven paradigm, Data science lifecycle

© 2017 Il-Yeol Song & Yongjun Zhu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Big Data and Data Science: Opportunities and Challenges of iSchools

Article Category: Perspective

Online veröffentlicht: 22. Aug. 2017

Seitenbereich: 1 - 18

Eingereicht: 25. März 2017

Akzeptiert: 18. Apr. 2017

DOI: https://doi.org/10.1515/jdis-2017-0011

SchlüsselwörterBig data, Data science, Information computing, The fourth Industrial Revolution, iSchool, Computational thinking, Data-driven paradigm, Data science lifecycle

© 2017 Il-Yeol Song & Yongjun Zhu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Big data, Data science, Information computing, The fourth Industrial Revolution, iSchool, Computational thinking, Data-driven paradigm, Data science lifecycle