A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming

By Greg Lusk. 2014

392 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c19625943788991408a2c2ba18aaaa27f62f0a55

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In Global and Planetary Change

Citations in the corpus

Algorithms and their others: Algorithmic culture in context (2016, background): “…climate data is not directly tied to the climate data itself, although it might inﬂuence the design of new sensors and data collection instruments (Edwards, 2010), but the algorithm by which Twitter determines the ‘‘trending topics’’ that it will report does exist in a feedback loop with the data…”
We get the algorithms of our ground truths: Designing referential databases in digital image processing (2017, positive): “In climatology, the tedious collection, standardization and compilation of weather data in order to produce accurate ground truths – ‘data images’ – of the Earth’s climate are crucial for the both the parametrization and evaluation of General Circulation Models (Edwards, 2013).”
Big data, bigger dilemmas: A critical review (2015, background): “Anything from instrument calibration and standards that guide the installation, development, and alignment of infrastructures (Edwards, 2010) to human habitual practices (Ribes & Jackson, 2013) or even intentional distortions (Bergstein, 2013) can disrupt the “rawness” of data.”
Critiquing Big Data: Politics, Ethics, Epistemology (2014, background): “…of big data, from the first instantiations of the U.S. census tracking human populations (Driscoll, 2012), the quantification of climate shifts (Edwards, 2010), the rapid analysis and projection of financial data (MacKenzie, 2006), and the complete capture of communications systems by…”
If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology (2013, background): “Global climate modeling, for example, depends upon consistent data collection of climate phenomena around the world at agreedupon times, locations, and variables [68].”