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期刊名:Big data & society

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ISSN:2053-9517

e-ISSN:2053-9517

IF/分区:7.8/Q1

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共收录本刊相关文章索引16
Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Age Poom,Olle Järv,Matthew Zook et al. Age Poom et al.
The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geographical aspect is important in understa...
Emily Bowe,Erin Simmons,Shannon Mattern Emily Bowe
In response to the ubiquitous graphs and maps of COVID-19, artists, designers, data scientists, and public health officials are teaming up to create counter-plots and subaltern maps of the pandemic. In this intervention, we describe the var...
Catherine D&#x;Ignazio,Lauren F Klein Catherine D&#x;Ignazio
This essay offers seven intersectional feminist principles for equitable and actionable COVID-19 data, drawing from the authors' prior work on data feminism. Our book, Data Feminism (D'Ignazio and Klein, 2020), offers seven principles which...
J Benjamin Hurlbut J Benjamin Hurlbut
This paper examines political norms and relationships associated with governance of pandemic risk. Through a pair of linked controversies over scientific access to H5N1 flu virus and genomic data, it examining the duties, obligations, and a...
Katie Harron,Chris Dibben,James Boyd et al. Katie Harron et al.
Linkage of population-based administrative data is a valuable tool for combining detailed individual-level information from different sources for research. While not a substitute for classical studies based on primary data collection, analy...
Sabina Leonelli Sabina Leonelli
Is big data science a whole new way of doing research? And what difference does data quantity make to knowledge production strategies and their outputs? I argue that the novelty of big data science does not lie in the sheer quantity of data...