Rapid urbanization presents multifaceted challenges to urban mobility,
necessitating innovative solutions for environmental and social
well-being. Despite extensive research, identifying critical urban
hotspots and proposing effective interventions remain active research
areas. This paper presents a knowledge engineering framework leveraging
urban data repositories to identify key infrastructure points and
promote sustainable, accessible mobility. Utilizing advanced data
science techniques, the study focuses on factors influencing pedestrian
and cyclist movements, aiming to foster active transportation and
improve citizens' health. Through a case study in Barcelona, the paper
demonstrates the efficacy of the approach while maintaining
generalizability. The data-driven analysis explores variations in
accessibility and mobility, addressing affordability issues and barriers
in emerging micro-mobility solutions. These insights contribute to
informed decision-making and policy formulation, facilitating global
transitions towards sustainable urban futures.