416 research outputs found

    Computing Storyline Visualizations with Few Block Crossings

    Full text link
    Storyline visualizations show the structure of a story, by depicting the interactions of the characters over time. Each character is represented by an x-monotone curve from left to right, and a meeting is represented by having the curves of the participating characters run close together for some time. There have been various approaches to drawing storyline visualizations in an automated way. In order to keep the visual complexity low, rather than minimizing pairwise crossings of curves, we count block crossings, that is, pairs of intersecting bundles of lines. Partly inspired by the ILP-based approach of Gronemann et al. [GD 2016] for minimizing the number of pairwise crossings, we model the problem as a satisfiability problem (since the straightforward ILP formulation becomes more complicated and harder to solve). Having restricted ourselves to a decision problem, we can apply powerful SAT solvers to find optimal drawings in reasonable time. We compare this SAT-based approach with two exact algorithms for block crossing minimization, using both the benchmark instances of Gronemann et al. and random instances. We show that the SAT approach is suitable for real-world instances and identify cases where the other algorithms are preferable.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

    On Minimizing Crossings in Storyline Visualizations

    Get PDF
    In a storyline visualization, we visualize a collection of interacting characters (e.g., in a movie, play, etc.) by xx-monotone curves that converge for each interaction, and diverge otherwise. Given a storyline with nn characters, we show tight lower and upper bounds on the number of crossings required in any storyline visualization for a restricted case. In particular, we show that if (1) each meeting consists of exactly two characters and (2) the meetings can be modeled as a tree, then we can always find a storyline visualization with O(nlogn)O(n\log n) crossings. Furthermore, we show that there exist storylines in this restricted case that require Ω(nlogn)\Omega(n\log n) crossings. Lastly, we show that, in the general case, minimizing the number of crossings in a storyline visualization is fixed-parameter tractable, when parameterized on the number of characters kk. Our algorithm runs in time O(k!2klogk+k!2m)O(k!^2k\log k + k!^2m), where mm is the number of meetings.Comment: 6 pages, 4 figures. To appear at the 23rd International Symposium on Graph Drawing and Network Visualization (GD 2015

    Block Crossings in Storyline Visualizations

    Full text link
    Storyline visualizations help visualize encounters of the characters in a story over time. Each character is represented by an x-monotone curve that goes from left to right. A meeting is represented by having the characters that participate in the meeting run close together for some time. In order to keep the visual complexity low, rather than just minimizing pairwise crossings of curves, we propose to count block crossings, that is, pairs of intersecting bundles of lines. Our main results are as follows. We show that minimizing the number of block crossings is NP-hard, and we develop, for meetings of bounded size, a constant-factor approximation. We also present two fixed-parameter algorithms and, for meetings of size 2, a greedy heuristic that we evaluate experimentally.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

    Story of a 'Storyline Visualization' in High School Readings

    Get PDF
    Storyline visualization, as a process of illustrating data that has a course of events via a visual medium, has been used in the area of film making for a very long time. Not so long ago, it has moved from the paper version to the digital word allowing for a wider usage. In this paper we propose its usage as a teaching tool in the area of literature reading for the Croatian class (primary language). We have conducted a preliminary research in five Croatian high schools of a different profile to see how storyline visualization, and visualization of school materials in general, affects students understanding of the material being studied. Each school participated with two groups of students where one group was exposed to the storyline visualization of a novel Prokleta avlija by Ivo Andrić [N=103 in total] during the reading period, and the other one was reading without the visualization [N=93 in total]. We will present our results taking into account students’ gender and type of a school

    In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals

    Get PDF
    Pathogen outbreaks (i.e., outbreaks of bacteria and viruses) in hospitals can cause high mortality rates and increase costs for hospitals significantly. An outbreak is generally noticed when the number of infected patients rises above an endemic level or the usual prevalence of a pathogen in a defined population. Reconstructing transmission pathways back to the source of an outbreak -- the patient zero or index patient -- requires the analysis of microbiological data and patient contacts. This is often manually completed by infection control experts. We present a novel visual analytics approach to support the analysis of transmission pathways, patient contacts, the progression of the outbreak, and patient timelines during hospitalization. Infection control experts applied our solution to a real outbreak of Klebsiella pneumoniae in a large German hospital. Using our system, our experts were able to scale the analysis of transmission pathways to longer time intervals (i.e., several years of data instead of days) and across a larger number of wards. Also, the system is able to reduce the analysis time from days to hours. In our final study, feedback from twenty-five experts from seven German hospitals provides evidence that our solution brings significant benefits for analyzing outbreaks
    corecore