IDEAS home Printed from https://ideas.repec.org/p/osf/lawarx/ps9de.html
   My bibliography  Save this paper

Commons at the Intersection of Peer Production, Citizen Science, and Big Data: Galaxy Zoo

Author

Listed:
  • Madison, Michael J

    (University of Pittsburgh)

Abstract

The knowledge commons research framework is applied to a case of commons governance grounded in research in modern astronomy. The case, Galaxy Zoo, is a leading example of at least three different contemporary phenomena. In the first place Galaxy Zoo is a global citizen science project, in which volunteer non-scientists have been recruited to participate in large-scale data analysis via the Internet. In the second place Galaxy Zoo is a highly successful example of peer production, sometimes known colloquially as crowdsourcing, by which data are gathered, supplied, and/or analyzed by very large numbers of anonymous and pseudonymous contributors to an enterprise that is centrally coordinated or managed. In the third place Galaxy Zoo is a highly visible example of data-intensive science, sometimes referred to as e-science or Big Data science, by which scientific researchers develop methods to grapple with the massive volumes of digital data now available to them via modern sensing and imaging technologies. This chapter synthesizes these three perspectives on Galaxy Zoo via the knowledge commons framework.

Suggested Citation

  • Madison, Michael J, 2017. "Commons at the Intersection of Peer Production, Citizen Science, and Big Data: Galaxy Zoo," LawArXiv ps9de, Center for Open Science.
    • Handle: RePEc:osf:lawarx:ps9de
    DOI: 10.31219/osf.io/ps9de
    as

    Download full text from publisher

    File URL: https://osf.io/download/59c6dab26c613b025ce24a6a/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/ps9de?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sue Nelson, 2008. "The Harvard computers," Nature, Nature, vol. 455(7209), pages 36-37, September.
    2. Franzoni, Chiara & Sauermann, Henry, 2014. "Crowd science: The organization of scientific research in open collaborative projects," Research Policy, Elsevier, vol. 43(1), pages 1-20.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Julian Koch & Simon Stisen, 2017. "Citizen science: A new perspective to advance spatial pattern evaluation in hydrology," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-20, May.
    2. Carolin Haeussler & Henry Sauermann, 2016. "The Division of Labor in Teams: A Conceptual Framework and Application to Collaborations in Science," NBER Working Papers 22241, National Bureau of Economic Research, Inc.
    3. Benedikt Fecher & Sascha Friesike & Marcel Hebing, 2014. "What Drives Academic Data Sharing?," SOEPpapers on Multidisciplinary Panel Data Research 655, DIW Berlin, The German Socio-Economic Panel (SOEP).
    4. Héloïse Berkowitz, 2020. "Participatory Governance for the Development of the Blue Bioeconomy in the Mediterranean Region," Working Papers hal-02555685, HAL.
    5. Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    6. Qin Ye & Xiaolei Xu, 2021. "Determining factors of cities’ centrality in the interregional innovation networks of China’s biomedical industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2801-2819, April.
    7. Haeussler, Carolin & Sauermann, Henry, 2013. "Credit where credit is due? The impact of project contributions and social factors on authorship and inventorship," Research Policy, Elsevier, vol. 42(3), pages 688-703.
    8. Kim, Hongbum & Shin, Dong-Hee & Lee, Daeho, 2015. "A socio-technical analysis of software policy in Korea: Towards a central role for building ICT ecosystems," Telecommunications Policy, Elsevier, vol. 39(11), pages 944-956.
    9. Mindel, Vitali & Overstreet, Robert E. & Sternberg, Henrik & Mathiassen, Lars & Phillips, Nelson, 2024. "Digital activism to achieve meaningful institutional change: A bricolage of crowdsourcing, social media, and data analytics," Research Policy, Elsevier, vol. 53(3).
    10. Benedikt Fecher & Gert G. Wagner, 2016. "Open Access, Innovation, and Research Infrastructure," Publications, MDPI, vol. 4(2), pages 1-8, June.
    11. Antonello Cammarano & Vincenzo Varriale & Francesca Michelino & Mauro Caputo, 2022. "Open and Crowd-Based Platforms: Impact on Organizational and Market Performance," Sustainability, MDPI, vol. 14(4), pages 1-26, February.
    12. Abhishek Nagaraj, 2018. "Does Copyright Affect Reuse? Evidence from Google Books and Wikipedia," Management Science, INFORMS, vol. 64(7), pages 3091-3107, July.
    13. Christian Matt & Christian Hoerndlein & Thomas Hess, 2017. "Let the crowd be my peers? How researchers assess the prospects of social peer review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(2), pages 111-124, May.
    14. Järvi, Kati & Almpanopoulou, Argyro & Ritala, Paavo, 2018. "Organization of knowledge ecosystems: Prefigurative and partial forms," Research Policy, Elsevier, vol. 47(8), pages 1523-1537.
    15. Ethan Mollick & Ramana Nanda, 2016. "Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the Arts," Management Science, INFORMS, vol. 62(6), pages 1533-1553, June.
    16. Jorge Faleiro & Edward Tsang, 2018. "Black Magic Investigation Made Simple: Monte Carlo Simulations and Historical Back Testing of Momentum Cross-Over Strategies Using FRACTI Patterns," Papers 1808.07949, arXiv.org.
    17. Huang, Jiekun, 2018. "The customer knows best: The investment value of consumer opinions," Journal of Financial Economics, Elsevier, vol. 128(1), pages 164-182.
    18. Kamilla Kohn Rådberg & Hans Löfsten, 2023. "Developing a knowledge ecosystem for large-scale research infrastructure," The Journal of Technology Transfer, Springer, vol. 48(1), pages 441-467, February.
    19. Susanne Beck & Maral Mahdad & Karin Beukel & Marion Poetz, 2019. "The Value of Scientific Knowledge Dissemination for Scientists—A Value Capture Perspective," Publications, MDPI, vol. 7(3), pages 1-23, July.
    20. Perkmann, Markus & Salandra, Rossella & Tartari, Valentina & McKelvey, Maureen & Hughes, Alan, 2021. "Academic engagement: A review of the literature 2011-2019," Research Policy, Elsevier, vol. 50(1).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:lawarx:ps9de. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/lawarxiv/discover .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.