Integrating landmarks into the communication of wayfinding services is an established strategy that enhances wayfinding efficiency and user confidence. In this context, we present a strategy for selecting landmarks for route descriptions that keeps the number of selected landmarks small. We argue that limiting the number of landmarks to be referred to in a route description can help to reduce the length and complexity of the description. Instead of selecting a different landmark located at each decision point, we reduce the selection to landmarks that can be seen from multiple decision points. We preferably choose those landmarks that are already clearly visible when approaching a decision point, thus optimizing advance visibility. We formalize an optimization problem that requires that at least one selected landmark is visible from each decision point. While minimizing the number of selected landmarks, we aim to maximize their advance visibility along the route. We show that our problem is NP-hard and present both an exact approach that uses integer linear programming and a greedy heuristic. In our experiments, we demonstrate that our approach can substantially reduce the number of selected landmarks compared to a baseline strategy. We determine a compromise between the optimization criteria and show that the heuristic generates high-quality solutions within a short running time.

Visualizing sets of elements and their relations is an important research area in information visualization. In this paper, we present MosaicSets: a novel approach to create Euler-like diagrams from non-spatial set systems such that each element occupies one cell of a regular hexagonal or square grid. The main challenge is to find an assignment of the elements to the grid cells such that each set constitutes a contiguous region. As use case, we consider the research groups of a university faculty as elements, and the departments and joint research projects as sets. We aim at finding a suitable mapping between the research groups and the grid cells such that the department structure forms a base map layout. Our objectives are to optimize both the compactness of the entirety of all cells and of each set by itself. We show that computing the mapping is NP-hard. However, using integer linear programming we can solve real-world instances optimally within a few seconds. Moreover, we propose a relaxation of the contiguity requirement to visualize otherwise non-embeddable set systems. We present and discuss different rendering styles for the set overlays. Based on a case study with real-world data, our evaluation comprises quantitative measures as well as expert interviews.