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Titlebook: Data Journeys in the Sciences; Sabina Leonelli,Niccolò Tempini Book‘‘‘‘‘‘‘‘ 2020 The Editor(s) (if applicable) and The Author(s) 2020 Big

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41#
發(fā)表于 2025-3-28 17:24:33 | 只看該作者
A Data Journey Through Dataset-Centric Population Genomicsf human genome diversity studies. I offer a model of data journeys to interpret the case. The model is comprised of three kinds of components: scientific data structures, data representations, and data journey narratives. The case study illustrates two visualizations that frame the dataset journey.
42#
發(fā)表于 2025-3-28 22:39:48 | 只看該作者
43#
發(fā)表于 2025-3-29 02:20:47 | 只看該作者
44#
發(fā)表于 2025-3-29 03:18:43 | 只看該作者
45#
發(fā)表于 2025-3-29 08:19:40 | 只看該作者
https://doi.org/10.1007/978-3-658-16847-6 produced and used by ISTI, we uncover yet another variety of what Paul Edwards (A vast machine: computer models, climate data, and the politics of global warming. MIT Press, Cambridge, MA, 2010) has described as “model-data symbiosis” in the practice of climate science.
46#
發(fā)表于 2025-3-29 13:21:30 | 只看該作者
Feedbacksysteme im Coachingprozess of . is multi-layered and scaffolded. as it depends on relations between various kinds of data, computing technologies, assumptions, theoretical scaffoldings, hypotheses and other features of the situation at hand.
47#
發(fā)表于 2025-3-29 18:42:57 | 只看該作者
The Evolution of Coaches as Artisansaphical information on the individuals measured, which allowed him to flexibly classify data in a variety of ways. It is this richness in structure, or “pattern data,” that explains why the data from Boas’s anthropometric projects remain valuable for researchers from a variety of disciplines to this very day.
48#
發(fā)表于 2025-3-29 21:46:20 | 只看該作者
49#
發(fā)表于 2025-3-30 01:12:58 | 只看該作者
50#
發(fā)表于 2025-3-30 07:15:51 | 只看該作者
Evaluating Data Journeys: Climategate, Synthetic Data and the Benchmarking of Methods for Climate Da produced and used by ISTI, we uncover yet another variety of what Paul Edwards (A vast machine: computer models, climate data, and the politics of global warming. MIT Press, Cambridge, MA, 2010) has described as “model-data symbiosis” in the practice of climate science.
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