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Data Science Thinking

The Next Scientific, Technological and Economic Revolution

  • Book
  • © 2018

Overview

Authors:
  1. Longbing Cao

    1. Advanced Analytics Institute, University of Technology Sydney, Sydney, Australia

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  • Offers a unique breadth of coverage, providing a comprehensive study of data science, technology and economy perspectives.
  • Presents rich and deep thinking and insights of data-driven research, innovation, industrialization, and opportunities
  • Addresses the needs of decisions-makers who are responsible for managing the new realm of data science.
  • Investigates the mindset and skillset of data scientists to help define the projected course of the data revolution

Part of the book series: Data Analytics (DAANA)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xx
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  2. Concepts and Thinking

    1. Front Matter

      Pages 1-1
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    2. The Data Science Era

      • Longbing Cao
      Pages 3-28

    3. What Is Data Science

      • Longbing Cao
      Pages 29-58

    4. Data Science Thinking

      • Longbing Cao
      Pages 59-90

  3. Challenges and Foundations

    1. Front Matter

      Pages 91-91
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    2. Data Science Challenges

      • Longbing Cao
      Pages 93-128

    3. Data Science Discipline

      • Longbing Cao
      Pages 129-160

    4. Data Science Foundations

      • Longbing Cao
      Pages 161-202

    5. Data Science Techniques

      • Longbing Cao
      Pages 203-234

  4. Industrialization and Opportunities

    1. Front Matter

      Pages 235-235
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    2. Data Economy and Industrialization

      • Longbing Cao
      Pages 237-262

    3. Data Science Applications

      • Longbing Cao
      Pages 263-292

    4. Data Profession

      • Longbing Cao
      Pages 293-327

    5. Data Science Education

      • Longbing Cao
      Pages 329-348

    6. Prospects and Opportunities in Data Science

      • Longbing Cao
      Pages 349-362

  5. Back Matter

    Pages 363-390
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Keywords

About this book

This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists?

Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.





Authors and Affiliations

  • Advanced Analytics Institute, University of Technology Sydney, Sydney, Australia

    Longbing Cao

About the author

Longbing Cao holds a PhD in Pattern Recognition and Intelligent Systems from the Chinese Academy of Sciences, China and another PhD in Computing Science at the University of Technology Sydney, Australia. He is a professor of data science at UTS. He has been working on data science and analytics research, education, development, and enterprise applications since he was a CTO and then joined academia. Motivated by real-world significant and common challenges, he has been leading the team to develop theories, tools and applications for new areas including non-IID learning, actionable knowledge discovery, behavior informatics, and complex intelligent systems, in addition to issues related to artificial intelligence, knowledge discovery, machine learning, and their enterprise applications. In data science and analytics, he initiated the Data Science and Knowledge Discovery lab at UTS in 2007, the Advanced Analytics Institute in 2011, the degrees Master of Analytics (Research) and PhD in Analytics in 2011 which are recognized as the world's first degrees in data science, the IEEE Task Force on Data Science and Advanced Analytics (DSAA) and IEEE Task Force on Behavior, Economic and Soci-cultural Computing in 2013, the IEEE Conference on Data Science and Advanced Analytics (DSAA), the ACM SIGKDD Australia and New Zealand Chapter in 2014, and the International Journal of Data Science and Analytics with Springer in 2015. He served as program and general chairs of conferences such as KDD2015. In enterprise data science innovation, his team has successfully delivered many large projects for government and business organizations in over 10 domains including finance/capital markets, banking, health and car insurance, health, telco, recommendation, online business, education, and the public sector including ATO, DFS, DHS, DIBP and IP Australia, resulting in billions of dollar savings and mentions in government, industry, media and OECD reports.

Bibliographic Information

  • Book Title: Data Science Thinking

  • Book Subtitle: The Next Scientific, Technological and Economic Revolution

  • Authors: Longbing Cao

  • Series Title: Data Analytics

  • DOI: https://doi.org/10.1007/978-3-319-95092-1

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing AG, part of Springer Nature 2018

  • Hardcover ISBN: 978-3-319-95091-4Published: 07 September 2018

  • Softcover ISBN: 978-3-030-06975-9Published: 31 January 2019

  • eBook ISBN: 978-3-319-95092-1Published: 17 August 2018

  • Series ISSN: 2520-1859

  • Series E-ISSN: 2520-1867

  • Edition Number: 1

  • Number of Pages: XX, 390

  • Number of Illustrations: 1 b/w illustrations, 61 illustrations in colour

  • Topics: Data Mining and Knowledge Discovery, Big Data/Analytics, Artificial Intelligence

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