CiteSeerX — TO BE PUBLISHED IN ADVANCES IN MACHINE LEARNING AND DATA MINING FOR ASTRONOMY Preprint typeset using LATEX style emulateapj v. 11/10/09 GALAXY ZOO: MORPHOLOGICAL CLASSIFICATION AND CITIZEN SCIENCE

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TO BE PUBLISHED IN ADVANCES IN MACHINE LEARNING AND DATA MINING FOR ASTRONOMY Preprint typeset using LATEX style emulateapj v. 11/10/09 GALAXY ZOO: MORPHOLOGICAL CLASSIFICATION AND CITIZEN SCIENCE

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@MISC{_tobe,
    author = {},
    title = {TO BE PUBLISHED IN ADVANCES IN MACHINE LEARNING AND DATA MINING FOR ASTRONOMY Preprint typeset using LATEX style emulateapj v. 11/10/09 GALAXY ZOO: MORPHOLOGICAL CLASSIFICATION AND CITIZEN SCIENCE},
    year = {}
}

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Abstract

We provide a brief overview of the Galaxy Zoo and Zooniverse projects, including a short discussion of the history of, and motivation for, these projects as well as reviewing the science these innovative internet-based citizen science projects have produced so far. We briefly describe the method of applying en-masse human pattern recognition capabilities to complex data in data-intensive research. We also provide a discussion of the lessons learned from developing and running these community–based projects including thoughts on future applications of this methodology. This review is intended to give the reader a quick and simple introduction to the Zooniverse.