The Database of Topographic Objects (DTO) is the official database of Poland for collecting and providing spatial data with the detail level of a topographic map. Polish national DTOs manage information about the spatial location and attribute values of geographic objects. Data in the DTO are the starting point for geographic information systems (GISs) for various central and local governments as well as private institutions. Every set of spatial data based on measurement-derived data is susceptible to uncertainty. Therefore, the widespread awareness of data uncertainty is of vital importance to all GIS users. Cartographic visualisation techniques are an effective approach to informing spatial dataset users about the uncertainty of the data. The objective of the research was to define a set of methods for visualising the DTO data uncertainty using expert know-how and experience. This set contains visualisation techniques for presenting three types of uncertainty: positional, attribute, and temporal. The positional uncertainty for point objects was presented using visual variables, object fill with hue colour and lightness, and glyphs placed at map symbol positions. The positional uncertainty for linear objects was presented using linear object contours made of dotted lines and glyphs at vertices. Fill grain density and contour crispness were employed to represent the positional uncertainty for surface objects. The attribute value uncertainty and the temporal uncertainty were represented using fill grain density and fill colour value. The proposed set of the DTO uncertainty visualisation methods provides a finite array of visualisation techniques that can be tested and juxtaposed. The visualisation methods were comprehensively evaluated in a survey among experts who use spatial databases. Results of user preference analysis have demonstrated that the set of the DTO data uncertainty visualisation techniques may be applied to the full extent. The future implementation of the proposed visualisation methods in GIS databases will help data users interpret values correctly.
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