Realism and Perceptions of Data Quality in Computer-Displayed Maps Tony Boughman, Geography Department; Collaborators: Dr. Sara Fabrikant, Geography; Dr. Mary Hegarty, Psychology University of California, Santa Barbara Continuum of “realism” from real-world observation to abstract representation Do people infer more accuracy and precision from maps that look more realistic? Study design abstract maps Most realistic is observing the real world itself as from the window of an airplane Maps may be so abstract as to lose most scale and geometric relationships to the real-world and retain only topological relationships The first, most realistic point along the continuum used in this study is orthogonal, true color, aerial photographs. These photographs are orthorectified, planar, have constant scale, and may be considered to be “image maps”. They represent photorealism. The second point chosen is shaded relief maps with naturalistic coloring and texturing. These maps are artistic and appear as we imagine the world to appear. The third point chosen is abstract maps with simpler coloring and less contextual information yet they retain representation of real-world geometry and scale. These maps are the type commonly found on internet location and direction-finding websites. Maps are abstractions of the real world, this is what makes them useful. Creators of geographic information are familiar with the inherent shortcomings in translating real- world observations into digital representations. Data used in creating maps come from many sources and vary in accuracy and precision. None of it is perfect therefore there is always some degree of uncertainty. With more powerful computing there seems to be a general movement toward more realistic display, but more realistic visual rendering does not necessarily mean that the underlying data are closer to reality, or more accurate and precise. Do map users think that a more realistic looking map is more accurate and precise and is therefore the result of higher quality data? Accuracy is the degree to which the location, spatial extent or geometric relationships of features or objects on a map is “truly” representative of the real world Precision is the degree to which the features or objects on a map represent the real world to a fine degree of spatial resolution (+/- inches vs. +/- miles) Subjects The participants are undergraduate students at UCSB recruited from the Geography Department Research Pool. The participants will be divided into three groups--three being the number of different stimulus types. Methods The study is focused on digitally-displayed maps specifically. All maps are viewed on a computer monitor. Each screen (web page) shows one map and its accompanying task and question. A paper questionnaire is used by each participant to record his or her answers. The questionnaire shows the same question as on the monitor and provides the spaces for answering and the rating scale for each question. Questions are given as tasks designed to focus attention on a certain aspect of each map. The ratings given by the rating scale are analyzed. Stimuli Three versions of maps varying in “realism”: 1. “Abstract” maps modeled on location and direction finding maps like those from Mapquest, Yahoo, MSN. The study maps were created using ArcMap GIS software from USGS data. 2. “Realistic” maps modeled on old Swiss painted maps and NPS maps by Tom Patterson. The study maps are not of the artistic quality of those, but along the same idea of maps that look the way we expect the world to look. They were created using ArcMap from USGS data. 3. Aerial orthophotographs or “image maps”, natural color, orthorectified, from USGS. Map scale was chosen as a compromise to work with both airphotos and shaded relief maps. Airphotos look better at larger scale (it seems the larger, the better) because recognizable objects can be identified. Shaded relief maps look better at small scale because most landforms are quite large and can be seen better from a greater distance. None of the maps have labeling. realistic maps image maps Examples of tasks, questions, and maps used in study Examine the road network on this map and estimate how long it would take to commute to the central city from each of the four locations I, J, K and L. Rank the locations from shortest commute time to longest commute time. Select either I, J, K or L for each. shortest _____ second shortest _____ third shortest _____ longest ______ How well does this map allow you to estimate the relative times it would take to commute from these locations? very poor for estimating allows estimation of commute commute times times with perfect accuracy How precisely and accurately does this map show the true location and shape of the river? How confident are you that this map shows the true location and shape of the river? no confidence that perfectly confident this this map shows river’s map shows river’s true location and shape true location and shape The distance along the red line is 10 kilometers. The distance is measured between the centers of the two intersections S and T. How confident are you that this distance is precise to within 1 kilometer? no confidence completely confident this distance is precise this distance is precise to within 1 kilometer How confident are you that this distance is precise to within 10 meters? no confidence completely confident this distance is precise this distance is precise Compare the lengths of the four bridges E, F, G, and H. Rank these bridges by size from longest to shortest. Select either E, F, G or H for each. Longest _____ second longest _____ third longest _____ shortest ______ How accurately does this map show the relative lengths of the bridges? Circle the number along the rating scale best corresponding to your answer very poor at showing shows lengths of bridges lengths of bridges with perfect accuracy This work is supported by the National Science Foundation’s Integrative Graduate Training Program in Interactive Digital Media (IGERT), Award number: DGE Relevance and applications The results of this study will provide insight into the effects of cartographic realism on people’s inferences of the underlying quality of the data. A relationship found here could possibly be employed in visualizing geographic data with regard to the conveyance of uncertainty. It may be feasible to use realism, or some component of realism, as a visual variable in situations that involve communicating the degree of data quality.