Galaxy Zoo: Morphological Classification and Citizen Science

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.

11 pages, 1 figure; to be published in Advances in Machine Learning and Data Mining for Astronomy

References in corpus (4)

• The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III
• LSST Science Book, Version 2.0
• Galaxy Zoo: Multi-Mergers and the Millennium Simulation
• Evidence for a Preferred Handedness of Spiral Galaxies

Cited by in corpus (9)

• Galaxy Zoo 2: detailed morphological classifications for 304,122 galaxies from the Sloan Digital Sky Survey
• Galaxy Zoo: Morphological Classifications for 120,000 Galaxies in HST Legacy Imaging
• Crowdsourced science: sociotechnical epistemology in the e-research paradigm
• Morphological Parameters of Spitzer Survey of Stellar Structure in Galaxies (S4G)
• Planet Four: Terrains - Discovery of Araneiforms Outside of the South Polar Layered Deposits
• Planet Four: Probing Springtime Winds on Mars by Mapping the Southern Polar CO${}_2$ Jet Deposits
• SuperCLASS -- III. Weak lensing from radio and optical observations in Data Release 1
• Collective Intelligence in Citizen Science -- A Study of Performers and Talkers
• When Scientists Become Social Scientists: How Citizen Science Projects Learn About Volunteers