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Depicting the Chaos – Navigating Complexity and Uncertainty in Urban Development Models

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The webinar will present the latest research findings on complexity and model theories.
The second part of the webinar will present ideas on how these findings can be applied to Urban Digital Twins.

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Guide to Model Land: A Guide to Ethical Questions for Modeling and Simulation in Urban Digital Twins

This "Guide to Model Land" is intended to be a practical guide to ethical issues concerning digital simulation models. It is divided into three sections: Entering Model Land, Navigating Model Land and Exiting Model Land. It was created based on extensive literature research and offers guidelines as well as references to further relevant literature.
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Ethische Grundlagen für Modellierung und Simulation

Dieser „Guide to Model Land“ wurde als Teil der transformativen experimentellen Forschung im Projekt „Connected Urban Twins“ am City Science Lab der HafenCity Universität Hamburg erstellt und beruht auf umfassenden theoretischen und praktischen Erfahrungen im Bereich Modellierung, Simulation, KI und Machine Learning.

The Key Learnings

Subsystems That Interact With Each Other

The complex system “city” is comprised of numerous interacting subsystems (e.g., social, ecological, technological subsystems) and is distinguished by a high degreee of non-linearity, emergence, hierarchies, nesting, and view dependency.

Depicting Using the Many-Models Approach

To map the complex “city” system in a Digital City Twin, it is recommended that a many-models approach be used. This entails the utilization of multiple digital models for a single system, which can be more effective in mapping the inherent uncertainties associated with their diversity.

Digital Simulation Models Are Characterized by Uncertainties

Every digital simulation model is characterized by uncertainties. There are various degress of uncertainty. The literature identifies five levels, ranging from complete certainty to complete ignorance. Levels four and five are reffered to as “deep uncertainty,” where it is no longer possible to assign probabilities of occurrence to certain scenarios.

Implications for Simulation Models

a) Uncertainties and assumptions in models should be transparent and comprehensible.
b) The purposes and validity of models should be clearly stated.
c) Models should be exchangeable and provisionable on a platorm (e.g., Urban Model Platform).
d) Tools for exploratory modeling and analysis should be provided for digital models of highly uncertain systems.
e) Models should be interoperable so that further development and reuse is possible.

More Information (German Site)

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Contact

Rico Herzog

“Transformative and Experimental Urban Research,” HafenCity University Hamburg

cut@sk.hamburg.de
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