Harvard Data Science Review launched

The Harvard Data Science Initiative (HDSI) and the MIT Press have launched  the Harvard Data Science Review (HDSR).

HDSR will combine features of a premier research journal, an educational publication and a popular magazine. The multimedia platform will make research, educational resources and commentary accessible to academics, professionals and the general public.

Key features

• Harvard Data Science Review will serve as a hub for high-quality work in data science
• Contributions from leading thinkers with direct applications for teaching, research, business, government, and more
• 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. 

Sample articles in the 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