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MIT Press and Harvard Data Science Initiative launch the Harvard Data Science Review

Open access journal to promote the latest research, educational resources, and commentary from leading minds in data science.
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Harvard Data Science Review is a new open-access journal published by MIT Press and hosted online via the multimedia platform PubPub, an initiative of the MIT Knowledge Futures group.
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Harvard Data Science Review is a new open-access journal published by MIT Press and hosted online via the multimedia platform PubPub, an initiative of the MIT Knowledge Futures group.

The following is adapted from a joint release from the MIT Press and the Harvard Data Science Initiative.

The MIT Press and the Harvard Data Science Initiative (HDSI) have announced the launch of the Harvard Data Science Review (HDSR). The open-access journal, published by MIT Press and hosted online via the multimedia platform PubPub, an initiative of the MIT Knowledge Futures group, will feature leading global thinkers in the burgeoning field of data science, making research, educational resources, and commentary accessible to academics, professionals, and the interested public. With demand for data scientists booming, HDSR will provide a centralized, authoritative, and peer-reviewed publishing community to service the growing profession.

The first issue features articles on topics ranging from authorship attribution of John Lennon-Paul 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. 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.

Combining features of a premier research journal, a leading educational publication, and a popular magazine, HDSR will leverage digital technologies and advances to facilitate author-reader interactions globally and learning across various media.

The Harvard Data Science Review will serve as a hub for high-quality work in the growing field of data science, noted by the Harvard Business Review as the "sexiest job of the 21st century." It will feature articles that provide expert overviews of complex ideas and topics from leading thinkers with direct applications for teaching, research, business, government, and more. It will highlight content in the form of 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; and short communications and letters to the editor.

The dynamic digital edition is freely available on the PubPub platform to readers around the globe.

Amy Brand, director of the MIT Press, states, “For too long the important work of data scientists has been opaque, appearing mainly in academic journals with limited reach. We are thrilled to partner with the Harvard Data Science Initiative to publish work that will have a deep impact on popular understanding of the growing field of data science. The Review will be an unparalleled resource for advancing data literacy in society.”

Francesca Dominici, the Clarence James Gamble Professor of Biostatistics, Population and Data Science, and David Parkes, the George F. Colony Professor of Computer Science, both at Harvard University, announce, “As codirectors of the Harvard Data Science Initiative, we’re thrilled for the launch of this new journal. With its rigorous and cross-disciplinary thinking, the Harvard Data ScienceReview will advance the new science of data. By sharing stories of positive transformational impact as well as raising questions, this collective endeavor will reveal the contours that will shape future research and practice.”

Xiao-li Meng, the Whipple V.N. Jones Professor of Statistics at Harvard and founding editor-in-chief of HDSR, explains, “The revolutionary ability to collect, process, and apply new analytics to extract powerful insights from data has a tremendous influence on our lives. However, hype and misinformation have emerged as unfortunate side effects of data science’s meteoric rise. The Harvard Data Science Review is designed to cut through the hype to engage readers with substantive and informed articles from the leading data science experts and practitioners, ranging from philosophers of ethics and historians of science to AI researchers and data science educators. In short, it is ‘everything data science and data science for everyone.’”

Elizabeth Langdon-Gray, inaugural executive director of HDSI, comments, “The Harvard Data Science Initiative was founded to foster collaboration in both research and teaching and to catalyze research that will benefit our society and economy. The Review plays a vital part in our effort to empower research progress and education globally and to solve some of the world’s most important challenges.”

The inaugural issue of HDSR will publish contributions from internationally renowned scholars and educators, as well as leading researchers in industry and government, such as Christine Borgman (University of California at Los Angeles), Rodney Brooks (MIT), Emmanuel Candes (Stanford University), David Donoho (Stanford University), Luciano Floridi (Oxford/The Alan Turing Institute), Alan M. Garber (Harvard), Barbara J. Grosz (Harvard), Alfred Hero (University of Michigan), Sabina Leonelli (University of Exeter), Michael I. Jordan (University of California at Berkeley), Andrew Lo (MIT), Maja Matarić (University of Southern California), Brendan McCord (U.S. Department of Defense), Nathan Sanders (WarnerMedia), Rebecca Willett (University of Chicago), and Jeannette Wing (Columbia University).

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