In advanced countries, such as Japan, the ageing of the bridge infrastructure, coupled with the shrinking of society due to declining birth rates and an ageing population, is a major challenge. In this context, there is an urgent need to formulate bridge abolition plans tailored to rural areas of Japan. However, the current situation is such that rational and standardized criteria for bridge abolition have not yet been established. This research aims at evaluating the need for bridge abolition within different regional government's maintenance frameworks, using various forms of big data, including ‘detour route data’. The methodology employs statistical analysis and unsupervised machine learning, specifically clustering analysis, and spatial visualization analysis with QGIS, to assess the regional government's maintenance situation and identify bridges that require abolition. As a result of the analysis, it became clear which municipalities could be considered for abolition more easily in comparison to others. Furthermore, it was found that more bridges suitable for abolition were identified in urban areas compared to mountainous regions. The pragmatic and accessible nature of the open data used is expected to significantly contribute to the development of infrastructure plans in rural areas.