localitycentric

Localitycentric is an adjective used to describe approaches, analyses, or designs that place emphasis on locality, defined as geographic or contextual proximity, as central to decisions. The term is not part of a fixed theory and may be applied differently across disciplines. When used, locality-centric implies prioritizing local conditions, constraints, and relationships over global or distant factors.

In computer science and information systems, locality-centric design or data placement refers to strategies that maximize data locality to reduce latency and improve performance. This can involve arranging data to be accessed near the processor that uses it, optimizing memory layouts for cache locality, or locating services and data stores close to their primary users or workloads.

In urban planning and public policy, locality-centric approaches focus on neighborhood or community levels, tailoring policies, services, and investments to the needs, capacities, and cultures of localities rather than applying uniform, global rules.

In data analysis and machine learning, locality-aware or local modeling concepts can align with locality-centric ideas by emphasizing local neighborhoods, context-aware features, or region-specific models to improve accuracy and relevance. While related in spirit, locality-centric is not a standardized term in these fields and may be used as a descriptive umbrella for locality-focused practices.

Etymology and usage: locality-centric is a contemporary coinage lacking a formal, universally accepted definition. It is typically used descriptively rather than as a formal theory, and its precise meaning depends on the disciplinary context. See also locality, data locality, and locality-sensitive techniques.