Data Modeling Design

Read e-book online A Vast Machine: Computer Models, Climate Data, and the PDF

By Paul N. Edwards

ISBN-10: 0262013924

ISBN-13: 9780262013925

The technological know-how at the back of international warming, and its background: how scientists realized to appreciate the ambience, to degree it, to track its prior, and to version its destiny.

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

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We are stuck with whatever data we have already collected, in whatever form, from whatever sources with whatever limitations they might have. We have to consolidate a global climate observing network not only prospectively but retrospectively, reassembling the motley collection of weather and climate records and reprocessing them as if they all existed only to help us in this moment. Since the 1980s, through a meticulous process of infrastructural inversion (see below), scientists have slowly and painfully consolidated these data, unearthing previously uncollected records and metadata (contextual information) and using them to create more comprehensive global datasets, to reduce inhomogeneities, and to render highly heterogeneous data sources into a common form.

GPS receivers in our phones and our cars pinpoint us precisely on the global grid. In all their incarnations, from Mercator projections to parlor globes to interactive GPS, maps are information technologies of the first order. 1 Behind the seeming immediacy of global maps and images lie vast bodies of complex and expensive collective and collaborative work and social learning accomplished over many centuries. This labor and this learning included not only invention, exploration, and surveying but also the slow spread, through practical use and formal education, of the graphical conventions, iconography, and social meaning of global maps.

Without the infrastructure, knowledge can decay or even disappear. Build up a knowledge infrastructure, maintain it well, and you get stable, reliable, widely shared understanding. 25 This is not an entirely new idea in science and technology studies, where scholars sometimes use the word ‘technoscience’ to capture the technological dimension of science as a knowledge practice. 26 I prefer the language of infrastructure, because it brings home fundamental qualities of endurance, reliability, and the takenfor-grantedness of a technical and institutional base supporting everyday work and action.

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A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming by Paul N. Edwards

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