Abstract

In modern data-driven geography, the question of validity is often reduced to a matter of ground truth data. However, for many spatio-temporal modeling purposes, such an account of validity is insufficient. Not only is ground truth often unavailable, data-driven approaches also fail to account for fictive modeling scenarios as well as for various purposes of modeling. Given this central role in science, it is somewhat surprising to find that validity remains a rather obscure concept. In this talk, I take a pragmatic (action-based) approach to the validity of maps. I argue that spatio-temporal models, as well as their cartographic representations, are valid only when delivering a valid answer to a particular kind of spatio-temporal question, corresponding to its information purpose. Questions are about experiments including spatio-temporal controls and measures. The latter constitute information purposes of maps. I discuss a corresponding question-based grammar to formally distinguish among predictions, retrodictions, projections, and retrojective questions. Based on various examples, I show how the grammar can be used to better understand the purposes and validity concerns of models that include maps.

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Materials

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References

Janich, P. (1985):  Protophysics of Time. Constructive Foundation and History of Time Measurement. Boston Studies in the Philosophy and History of Science (30). Springer. https://link.springer.com/book/10.1007/978-94-009-5189-1
Janich, P. (2006). What is information? (Vol. 55). University of Minnesota Press
Scheider, S. and Verstegen, J.A. (2024). What Is a Spatio-Temporal Model Good For?: Validity as a Function of Purpose and the Questions Answered by a Model. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 7:1-7:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPIcs.COSIT.2024.7
Top, E., Scheider, S., Xu, H., Nyamsuren, E., & Steenbergen, N. (2022). The semantics of extensive quantities within geographic information. Applied Ontology, 17(3), 337-364. https://doi.org/10.3233/AO-220268
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Scheider, S., & Richter, K-F. (2023). Pragmatic GeoAI: Geographic Information as Externalized Practice. KI – Kunstliche Intelligenz. https://doi.org/10.1007/s13218-022-00794-2