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Visualizing spatial data on small-screen devices such as smartphones andsmartwatches poses new challenges in computational cartography. The currentinterfaces for map exploration require their users to zoom in and outfrequently. Indeed, zooming and panning are tools suitable for choosing the mapextent corresponding to an area of interest. They are not as suitable, however,for resolving the graphical clutter caused by a high feature density sincezooming in to a large map scale leads to a loss of context. Therefore wepresent new external labeling methods that allow navigating through dense setsof points of interest while keeping the current map extent fixed. We provide aunified model, in which labels are placed at the boundary of the map andvisually associated with the corresponding features via connecting lines, whichare called leaders. Since the screen space is limited, labeling all features atthe same time is impractical. Therefore, at any time, we label a subset of thefeatures. We offer interaction techniques to change the current selection offeatures systematically and, thus, give the user access to all features. Wedistinguish three methods, which allow the user either to slide the labelsalong the bottom side of the map or to browse the labels based on pages orstacks. We present a generic algorithmic framework that provides us with thepossibility of expressing the different variants of interaction techniques asoptimization problems in a unified way. We propose both exact algorithms andfast and simple heuristics that solve the optimization problems taking intoaccount different criteria such as the ranking of the labels, the total leaderlength and the distance between leaders. We experimentally evaluate thesealgorithms and discuss the three variants with respect to their strengths andweaknesses proving the flexibility of the presented algorithmic framework.

Zoomless Maps: External Labeling Methods for the Interactive Exploration of Dense Point Sets at a Fixed Map Scale