Abstract The era of Big Data has given rise to a massive amount of data containing spatio-temporal information, such as video data, traffic data, and social media data. Current research on spatio-temporal data mainly focuses on the spatial information, while temporal information is usually processed in an auxiliary manner using simple approaches. In order to solve the existing problems in the current time coding schemes, this paper proposed a new type of integer coding method for the time segments called Multi-scale Time Segment Integer Coding (MTSIC). Based on the tree structures and the sorting of the integers, this method is able to describe various temporal relationships among different scales of time segments, such as the start and end, containment/inclusion, which makes it a uniform integer coding scheme for multiple scales of time information. Furthermore, this paper has studied on the MTSIC-based calculations and conversions, including the hierarchical calculations, the hierarchical regression calculations, the conversion between the conventional time coding schemes, the calculations on temporal relationships, and the conversion of arbitrary time spans. These efforts support highly efficient calculations and queries based on the time segments. Preliminary investigations have also been conducted on the potential applications and prospects of the MTSIC method. The results of experiments demonstrated that the implementation of MTSIC is simple and reliable, and MTSICs are easily converted into conventional expressions of time. Additionally, the MTSIC method also exhibits a very high level of efficiency in terms of the time needed to query and perform computations on time values.