Galaxy Zoo: Clump Scout – Design and first application of a two-dimensional aggregation tool for citizen science

Author:

Dickinson Hugh1ORCID,Adams Dominic2ORCID,Mehta Vihang23ORCID,Scarlata Claudia2ORCID,Fortson Lucy2ORCID,Serjeant Stephen1ORCID,Krawczyk Coleman4ORCID,Kruk Sandor5ORCID,Lintott Chris6ORCID,Mantha Kameswara Bharadwaj2ORCID,Simmons Brooke D7ORCID,Walmsley Mike8ORCID

Affiliation:

1. School of Physical Sciences, The Open University , Milton Keynes, MK7 6AA, UK

2. School of Physics and Astronomy, University of Minnesota , 116 Church Street SE, Minneapolis, MN 55455, USA

3. IPAC , Mail Code 314-6, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, 91125, USA

4. Institute of Cosmology & Gravitation, University of Portsmouth , Dennis Sciama building, Portsmouth, PO1 SFX, UK

5. Max-Planck-Institut für extraterrestrische Physik (MPE) , Giessenbachstrasse 1, D-85748 Garching bei München, Germany

6. Oxford Astrophysics, University of Oxford , Denys Wilkinson Building, Keble Road, Oxford, OX1 3RH, UK

7. Physics Department, Lancaster University , Lancaster, LA1 4YB, UK

8. Jodrell Bank Centre for Astrophysics, Department of Physics & Astronomy, University of Manchester , Manchester M13 9PL, UK

Abstract

ABSTRACT Galaxy Zoo: Clump Scout  is a web-based citizen science project designed to identify and spatially locate giant star forming clumps in galaxies that were imaged by the Sloan Digital Sky Survey Legacy Survey. We present a statistically driven software framework that is designed to aggregate two-dimensional annotations of clump locations provided by multiple independent Galaxy Zoo: Clump Scout volunteers and generate a consensus label that identifies the locations of probable clumps within each galaxy. The statistical model our framework is based on allows us to assign false-positive probabilities to each of the clumps we identify, to estimate the skill levels of each of the volunteers who contribute to Galaxy Zoo: Clump Scout and also to quantitatively assess the reliability of the consensus labels that are derived for each subject. We apply our framework to a data set containing 3561 454 two-dimensional points, which constitute 1739 259 annotations of 85 286 distinct subjects provided by 20 999 volunteers. Using this data set, we identify 128 100 potential clumps distributed among 44 126 galaxies. This data set can be used to study the prevalence and demographics of giant star forming clumps in low-redshift galaxies. The code for our aggregation software framework is publicly available at: https://github.com/ou-astrophysics/BoxAggregator

Funder

European Union

Horizon 2020

Science and Technology Facilities Council

Alan Turing Institute

National Science Foundation

National Aeronautics and Space Administration

Alfred P. Sloan Foundation

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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