Harvard Data Science Initiative (HDSI) Announces Launch of the Harvard Data Science Review

From the HDSI:

Today, the Harvard Data Science Initiative announced the launch of the first issue of the Harvard Data Science Review, the inaugural publication of the HDSI published by MIT Press.

Combining features of a premier research journal, a leading educational publication, and a popular magazine, HDSR leverages digital technologies and data visualizations to facilitate author-reader interactions globally. The first issue of the freely available digital edition features articles on topics ranging from authorship attribution of Lennon-McCartney songs to machine learning models for predicting drug approvals to artificial intelligence.

More From MIT Press Announcement

HDSR will prioritize quality over quantity, with a primary emphasis on substance and readability, attracting readers via inspiring, informative, and intriguing papers, essays, stories, interviews, debates, guest columns, and data science news. By doing so, HDSR intends to help define and shape the profession as a scientifically rigorous and globally impactful multidisciplinary field.

Harvard Data Science Review Key Features:

• The Harvard Business Review has called data science the “sexiest job of the 21st century” and the Harvard Data Science Review will serve as a hub for high-quality work in this growing field.
• Features contributions from leading thinkers with direct applications for teaching, research, business, government, and more.
• Publishes articles that provide expert overviews of complex ideas and topics.
• Includes content in the following categories:
  • Commentaries, overviews, and debates intended for a wide readership
    • Fundamental philosophical, theoretical, and methodological research
    • Innovations and advances in learning, teaching, and communicating data science
    • Short communications and letters to the editor
• The dynamic digital edition is freely available on the PubPub platform to readers around the globe.

Direct to Some of the Articles Published in First Issue

• A trio of articles on the “Data Life Cycle” by Christine Borgman, UCLA; Sabina Leonelli University of Exeter; and Jeannette Wing, Columbia University
• “A Data in the Life: Authorship Attribution in Lennon-McCartney Songs” by Mark Glickman, Harvard University; Jason Brown, Dalhousie University; Ryan Song, Harvard University
• “Machine-learning with Statistical Imputation for Predicting Drug Approvals” by Andrew W. Lo, MIT; Kien Wei Siah, MIT; and Chi Heem Wong, MIT

Featured Articles on AI:

• “Artificial Intelligence—The Revolution Hasn’t Happened Yet” by Michael I. Jordan, University of California, Berkeley, with 11 discussants from pioneering roboticists to leading AI researchers and Jordan’s rejoinder.
• “A Unified Framework of Five Principles for AI in Society” ­by Luciano Floridi and Josh Cowls, University of Oxford and The Alan Turing Institute
• “Mining the Past: Artificial Intelligence” by Stephanie Dick, University of Pennsylvania

Direct to Complete Table on Contents

Filed under: Data Files, Interviews, Journal Articles, News