A global indoor positioning system (GIPS) is a system that provides positioning services in most buildings in villages and cities globally. Among the various indoor positioning techniques, WLAN-based location fingerprinting has attracted considerable attention because of the wide availability of WLAN and relatively high resolution of the fingerprint-based positioning techniques. This paper introduces methods and tools to construct a GIPS by using WLAN fingerprinting. An unsupervised learning-based method is adopted to construct radio maps using fingerprints collected via crowdsourcing, and a probabilistic indoor positioning algorithm is developed for the radio maps constructed with the crowdsourced fingerprints. Along with these techniques, collecting indoor and radio maps of buildings in villages and cities is essential for a GIPS. This paper aims to collect indoor and radio maps from volunteers who are interested in deploying indoor positioning systems for their buildings. The methods and tools for the volunteers are also described in the process of developing an indoor positioning system within the larger GIPS. An experimental GIPS, named KAIST indoor locating system (KAILOS), was developed integrating the methods and tools. Then indoor navigation systems for a university campus and a large-scale indoor shopping mall were developed on KAILOS, revealing the effectiveness of KAILOS in developing indoor positioning systems. The more volunteers who participate in developing indoor positioning systems on KAILOS-like systems, the sooner GIPS will be realized.