One of the crucial tasks of geodetic science in the modern era is to provide its unified spatial and temporal reference to geoinformation science and its wide area of application fields. In the dissertation we elaborate a possible way of analysis of the geolocation significance as a function of time and present an aid in spatio-temporal quality evaluation through the use of spatio-temporal evaluation matrices (STEM) and the index of spatio-temporal anticipations (INSTANT) matrices. The global geospatial community is investing substantial effort in providing tools for geospatial data quality information analysis and systematizing the criteria for geospatial data quality. The importance of these activities is increasing, especially in the last decade, which has witnessed an enormous expansion of geospatial data use in general and especially among mass users. Although geospatial data producers are striving to define and present data-quality standards to users and users increasingly need to assess the fitness for use of the data, the success of these activities is still far from what is expected or required. As a consequence, neglect or misunderstanding of data quality among users results in misuse or risks. With the help of the simple tools of STEM and INSTANT matrices, geospatial data producers can systematically categorize and visualize the granularity of their spatio-temporal data, and users can present their requirements in the same way using business intelligence principles and a Web 2.0 approach. In the dissertation we present the basic principles with numerous categorized examples and also briefly describe interesting potential further applied research activities.