From: Heather Staines <[log in to unmask]>
Date: Mon, 12 Aug 2019 09:47:48 -0400

Please pardon any cross-posting.


The Harvard Data Science Initiative <https://datascience.harvard.edu/>
(HDSI) and the MIT Press <https://mitpress.mit.edu/> have just
launched the *Harvard
Data Science Review* <https://hdsr.mitpress.mit.edu/> (HDSR), hosted on
PubPub <http://PubPub.> an open source community platform. Combining
features of a premier research journal, a leading educational publication,
and a popular magazine, *HDSR* provides a centralized, authoritative, and
peer-reviewed publishing community to service the growing profession.



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 (AI). Future content will have a similar range of general
interest, academic, and professional content intended to foster dialogue
among researchers, educators, and practitioners about data science
research, practice, literacy, and workforce development.



Sample articles in the inaugural issue:



●      A trio of articles on “*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

●      “*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

●      *“Highlights of the National Academics Report on ‘Data Science for
Undergraduates: Opportunities and Options’” *Laura Haas, University of
Massachusetts, and Alfred Hero, University of Michigan, interviewed by Rob
Lue, Harvard University

●      *“A Balanced Perspective on Prediction and Inference for Data
Science in Industry” *Nathan E. Sanders, WarnerMedia Applied Analytics



Read the full issue now at hdsr.mitpress.mit.edu.


Thanks,

Heather