Varieties of Data-Centric Science: Regional Climate Modeling and Model Organism Research.

Modern science's ability to produce, store, and analyze big datasets is changing the way that scientific research is practiced. Philosophers have only begun to comprehend the changed nature of scientific reasoning in this age of "big data." We analyze data-focused practices in biology and climate mo...

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Publicado en:Philosophy of Science Vol. 89; no. 4; pp. 802 - 824
Autores principales: Lloyd, Elisabeth, Lusk, Greg, Gluck, Stuart, McGinnis, Seth
Formato: Artículo
Publicado: Cambridge University Press Oct2022
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Varieties of Data-Centric Science: Regional Climate Modeling and Model Organism Research.
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        au:
          Lloyd, Elisabeth
          Lusk, Greg
          Gluck, Stuart
          McGinnis, Seth
        affil:
          Indiana University, Department of History and Philosophy of Science and Medicine, Bloomington, IN, USA
          Durham University, Department of Philosophy, Durham, UK
          Johns Hopkins University, Center for Talented Youth
          National Center for Atmospheric Research, Boulder, CO, USA
      su:
        Atmospheric models
        Climatology
        Scientific ability
        Big data
      sug:
        subj:
          Atmospheric models
          Climatology
          Scientific ability
          Big data
      ab: Modern science's ability to produce, store, and analyze big datasets is changing the way that scientific research is practiced. Philosophers have only begun to comprehend the changed nature of scientific reasoning in this age of "big data." We analyze data-focused practices in biology and climate modeling, identifying distinct species of data-centric science: phenomena-laden in biology and phenomena-agnostic in climate modeling, each better suited for its own domain of application, though each entail trade-offs. We argue that data-centric practices in science are not monolithic because the opportunities and challenges presented by big data vary across scientific domains.
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    language: English
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