A Journal for Human and Machine
Authors
Hendler, James A.
Ding, Ying
Mons, Barend
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Issue Date
2019-03-01
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Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
Full Citation
James Hendler, Ying Ding, Barend Mons; A Journal for Human and Machine. Data Intelligence 2019; 1 (1): 1–5. doi: https://doi.org/10.1162/dint_e_00001
Abstract
It is with great pride that the Chinese Academy of Sciences and the MIT Press bring you this new journal of Data Intelligence. This journal has at least two major purposes that we hope embrace. First, it will embrace the traditional role of a journal in helping to facilitate the communication of research and best practices in scientific data sharing, especially across disciplines, an area that is continually growing in importance for the modern practice of science. Second, we will be experimenting with new methods of enhancing the sharing of this communication, and examples of the field, by utilizing the increasing power of intelligent computing systems to further facilitate the growth of the field. The journals’ title, combining “data,” the field we will support, and “intelligence,” a means to that end, is meant to connote this growing interaction.
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Publisher
MIT Press