When open data is a Trojan Horse: The weaponization of transparency in science and governance

被引:31
|
作者
Levy, Karen E. C. [1 ,2 ]
Johns, David Merritt [1 ,3 ]
机构
[1] Data & Soc Res Inst, New York, NY 10011 USA
[2] Cornell Univ, New York, NY 10021 USA
[3] Columbia Univ, New York, NY USA
来源
BIG DATA & SOCIETY | 2016年 / 3卷 / 01期
关键词
Transparency; openness; data; policy; governance; science;
D O I
10.1177/2053951715621568
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Openness and transparency are becoming hallmarks of responsible data practice in science and governance. Concerns about data falsification, erroneous analysis, and misleading presentation of research results have recently strengthened the call for new procedures that ensure public accountability for data-driven decisions. Though we generally count ourselves in favor of increased transparency in data practice, this Commentary highlights a caveat. We suggest that legislative efforts that invoke the language of data transparency can sometimes function as "Trojan Horses'' through which other political goals are pursued. Framing these maneuvers in the language of transparency can be strategic, because approaches that emphasize open access to data carry tremendous appeal, particularly in current political and technological contexts. We illustrate our argument through two examples of pro-transparency policy efforts, one historical and one current: industry-backed "sound science'' initiatives in the 1990s, and contemporary legislative efforts to open environmental data to public inspection. Rules that exist mainly to impede science-based policy processes weaponize the concept of data transparency. The discussion illustrates that, much as Big Data itself requires critical assessment, the processes and principles that attend it-like transparency-also carry political valence, and, as such, warrant careful analysis.
引用
收藏
页码:1 / 6
页数:6
相关论文
共 50 条
  • [21] Open peer review: promoting transparency in open science
    Wolfram, Dietmar
    Wang, Peiling
    Hembree, Adam
    Park, Hyoungjoo
    [J]. SCIENTOMETRICS, 2020, 125 (02) : 1033 - 1051
  • [22] Open peer review: promoting transparency in open science
    Dietmar Wolfram
    Peiling Wang
    Adam Hembree
    Hyoungjoo Park
    [J]. Scientometrics, 2020, 125 : 1033 - 1051
  • [23] Open Science Towards Greater Transparency and Openness in Science
    Maedche, Alexander
    Elshan, Edona
    Hoehle, Hartmut
    Lehrer, Christiane
    Recker, Jan
    Sunyaev, Ali
    Sturm, Benjamin
    Werth, Oliver
    [J]. BUSINESS & INFORMATION SYSTEMS ENGINEERING, 2024, 66 (04) : 517 - 532
  • [24] Open data: Accountability and transparency
    Mayernik, Matthew S.
    [J]. BIG DATA & SOCIETY, 2017, 4 (02): : 1 - 5
  • [25] Data Science Data Governance
    Kroll, Joshua A.
    [J]. IEEE SECURITY & PRIVACY, 2018, 16 (06) : 61 - 70
  • [26] Introduction: Gift horse or Trojan horse? Social science perspectives on evidence-based health care
    Lambert, Helen
    Gordon, Elisa J.
    Bogdan-Lovis, Elizabeth A.
    [J]. SOCIAL SCIENCE & MEDICINE, 2006, 62 (11) : 2613 - 2620
  • [27] Embracing Open Science and Transparency in Health Psychology
    Hagger, Martin S.
    [J]. HEALTH PSYCHOLOGY REVIEW, 2019, 13 (02) : 131 - 136
  • [28] Increasing transparency through open science badges
    Jarrad, Frith
    Main, Ellen
    Burgman, Mark
    [J]. CONSERVATION BIOLOGY, 2021, 35 (03) : 764 - 765
  • [29] Exploring openness in data and science: What is open, to whom, when, and why?
    Pasquetto, Irene V.
    Sands, Ashley E.
    Borgman, Christine L.
    [J]. Proceedings of the Association for Information Science and Technology, 2015, 52 (01) : 1 - 2
  • [30] Open data: towards full transparency
    Timothy H. Parker
    Shinichi Nakagawa
    Jessica Gurevtich
    [J]. Nature, 2016, 538 : 459 - 459