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Towards a Taxonomy of the Model-Ladenness of Data

Published online by Cambridge University Press:  01 January 2022

Alisa Bokulich
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Abstract

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are data-laden and data are model-laden. In this article I elaborate and defend the second, more controversial, component of the symbiosis view and construct a taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than so-called raw data and, hence, beneficially serve the epistemic aims of science.

Type
Models and Modeling
Information
Philosophy of Science , Volume 87 , Issue 5: PSA 2018 - Proceedings of the 2018 biennial meeting of the Philosophy of Science Association. Part II Symposia Papers , December 2020 , pp. 793 - 806
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

This article was written while I was a visiting researcher at the Institute for Advanced Study at Durham University, and I gratefully acknowledge the financial support of the European Union COFUND Senior Research Fellowship, under EU grant 609412. I am especially grateful to Wendy Parker for serving as my host while there and for many stimulating discussions about this topic.

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