عنوان انگلیسی مقاله:
Conceptualizations of Big Data and their epistemological claims in healthcare: A discourse analysis
ترجمه فارسی عنوان مقاله:
مفهوم سازی داده های بزرگ و ادعاهای معرفت شناختی آنها در مراقبت های بهداشتی: یک تحلیل گفتمان
SAGE Publications, Big Data & Society July–December 2018: 1–21
Marthe Stevens, Rik Wehrens and Antoinette de Bont
In recent years, the healthcare field welcomed an emerging field of practices captured under the umbrella term ‘Big Data’.
This term is surrounded with positive rhetoric and promises about the ability to analyse real-world data quickly and
comprehensively. Such rhetoric is highly consequential in shaping debates on Big Data. While the fields of Science and
Technology Studies and Critical Data Studies have been instrumental in elaborating the neglected and problematic
dimensions of Big Data, it remains an open question how and to what extent such insights become embedded in
other fields. In this paper, we analyse the epistemological claims that accompany Big Data in the healthcare domain.
We systematically searched scientific literature and selected 206 editorials as these reflect on developments in the
domain. Through an interpretive analysis, we construct five ideal-typical discourses that all frame Big Data in specific
ways. Three of the discourses (the modernist, instrumentalist and pragmatist) frame Big Data in positive terms and
disseminate a compelling rhetoric. Metaphors of ‘capturing’, ‘illuminating’ and ‘harnessing’ data presume that Big Data are
benign and leading to valid knowledge. The scientist and critical-interpretive discourses question the objectivity and
effectivity claims of Big Data. Metaphors of ‘selecting’ and ‘constructing’ data illustrate another political message, framing
Big Data as limited. We conclude that work in the critical-interpretive discourse has not broadly infiltrated the medical
domain. Ways to better integrate aspects of the discourse in the healthcare domain are urgently needed.
Keywords: Big Data | evidence | healthcare | discourse analysis | systematic review | editorials