An iSchool approach to data science: Human-centered, socially responsible, and context-driven

Chirag Shah, Theresa Anderson, Loni Hagen, Yin Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

The Information Schools, also referred to as iSchools, have a unique approach to data science with three distinct components: human-centeredness, socially responsible, and rooted in context. In this position paper, we highlight and expand on these components and show how they are integrated in various research and educational activities related to data science that are being carried out at iSchools. We argue that the iSchool way of doing data science is not only highly relevant to the current times, but also crucial in solving problems of tomorrow. Specifically, we accentuate the issues of developing insights and solutions that are not only data-driven, but also incorporate human values, including transparency, privacy, ethics, fairness, and equity. This approach to data science has meaningful implications on how we educate the students and train the next generation of scholars and policymakers. Here, we provide some of those design decisions, rooted in evidence-based research, along with our perspective on how data science is currently situated and how it should be advanced in iSchools.

Original languageEnglish (US)
Pages (from-to)793-796
Number of pages4
JournalJournal of the Association for Information Science and Technology
Volume72
Issue number6
DOIs
StatePublished - Jun 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences

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