multiskalamuppföljningar

Multiskalamupp is a neologism used to denote a hypothetical interdisciplinary framework for analyzing phenomena that unfold across multiple spatial and temporal scales. The term combines elements suggesting many scales and a modular, uncertain typology, and it is not widely standardized, appearing mainly in avant-garde theoretical writing and some digital-media contexts. In its most common articulation, multiskalamupp aims to unify macro-level dynamics with micro-level mechanisms by coupling models that operate at different scales through iterative feedback and data fusion. Proponents argue that it helps bridge gaps between disciplines such as ecology, urban planning, complex systems, and data science, enabling more resilient design and risk assessment by preserving scale-specific mechanisms while allowing cross-scale interaction.

There is no single formalism; definitions vary from a methodological stance to a loosely structured research program. Core principles include explicit attention to scale definitions, modular architectures, interoperable data protocols, and transparent uncertainty propagation across layers. Critics note that without a strong mathematical foundation, the concept risks vagueness and fragmentation across fields.

Use cases often cited include urban resilience analyses, climate-adaptation planning, and multi-scale simulations in ecological systems. To advance the concept, scholars advocate concrete case studies, standardized metrics for cross-scale effects, and clearer articulation of scope and boundaries.

See also: multiscale modeling, systems theory, transdisciplinarity, complexity science, data fusion.