This paper discusses the judgement of data quality for a collection of 132 geodatasets and evaluates different methods of visualising the results for presentation alongside the datasets themselves in a visualisation tool. The data has been accumulated within the BIOTA East Africa subproject E02 for research into the longer-term forest cover change for the Kakamega-Nandi forest complex in west Kenya and requires quality assessment to enable future critical use of the geodatabase. The data sources comprise satellite imagery, aerial photography, topographic maps and drafts, forestry maps, map sketches, thematic maps, and datasets derived from fieldwork including oral histories. The database includes image, raster and vector datasets, all of which are judged individually by one person according to the six data quality parameters of lineage, positional accuracy, attribute accuracy, logical consistency, completeness, and temporal information. Their selection is based on a literature review. Four of the judgements make use of a 1 to 5 ranking scale. For five of the six parameters additional information is given. The statistical assessment reveals distinct patterns. For example, the older maps generally have a poorer positional accuracy, and forestry maps are often both incomplete and have a poor date reliability. A second literature review helps to select ten different cartographic methods of visualising the quality parameters in diagrammatic form. These are reviewed against such criteria as universal suitability, memorability, and the potential for easy combination with text. The methods are then assessed to select the best medium in which to illustrate the six quality criteria in a complex diagram for each dataset. With memorability, clarity and ease of use foremost in mind, a traffic light system of visualisisation is selected as the best option for five quality parameters while a slider is chosen to present the completeness