2021-02, Meschenmoser, Philipp, Buchmüller, Juri F., Seebacher, Daniel, Wikelski, Martin, Keim, Daniel A.

Segmenting biologging time series of animals on multiple temporal scales is an essential step that requires complex techniques with careful parameterization and possibly cross-domain expertise. Yet, there is a lack of visual-interactive tools that strongly support such multi-scale segmentation. To close this gap, we present our MultiSegVA platform for interactively defining segmentation techniques and parameters on multiple temporal scales. MultiSegVA primarily contributes tailored, visual-interactive means and visual analytics paradigms for segmenting unlabeled time series on multiple scales. Further, to flexibly compose the multi-scale segmentation, the platform contributes a new visual query language that links a variety of segmentation techniques. To illustrate our approach, we present a domain-oriented set of segmentation techniques derived in collaboration with movement ecologists. We demonstrate the applicability and usefulness of MultiSegVA in two real-world use cases from movement ecology, related to behavior analysis after environment-aware segmentation, and after progressive clustering. Expert feedback from movement ecologists shows the effectiveness of tailored visual-interactive means and visual analytics paradigms at segmenting multi-scale data, enabling them to perform semantically meaningful analyses. A third use case demonstrates that MultiSegVA is generalizable to other domains.

2020, Kraus, Matthias, Angerbauer, Katrin, Buchmüller, Juri F., Schweitzer, Daniel, Keim, Daniel A., Sedlmair, Michael, Fuchs, Johannes

Heatmaps are a popular visualization technique that encode 2D density distributions using color or brightness. Experimental studies have shown though that both of these visual variables are inaccurate when reading and comparing numeric data values. A potential remedy might be to use 3D heatmaps by introducing height as a third dimension to encode the data. Encoding abstract data in 3D, however, poses many problems, too. To better understand this tradeoff, we conducted an empirical study (N=48) to evaluate the user performance of 2D and 3D heatmaps for comparative analysis tasks. We test our conditions on a conventional 2D screen, but also in a virtual reality environment to allow for real stereoscopic vision. Our main results show that 3D heatmaps are superior in terms of error rate when reading and comparing single data items. However, for overview tasks, the well-established 2D heatmap performs better.

2020, Schlegel, Udo, Jentner, Wolfgang, Buchmüller, Juri F., Cakmak, Eren, Castiglia, Giuliano, Canepa, Renzo, Petralli, Simone, Oneto, Luca, Keim, Daniel A., Anguita, Davide

Train operators are responsible for maintaining and following the schedule of large-scale railway transport systems. Disruptions to this schedule imply conflicts that occur when two trains are bound to use the same railway segment. It is upon the train operator to decide which train must go first to resolve the conflict. As the railway transport system is a large and complex network, the decision may have a high impact on the future schedule, further train delay, costs, and other performance indicators. Due to this complexity and the enormous amount of underlying data, machine learning models have proven to be useful. However, the automated models are not accessible to the train operators which results in a low trust in following their predictions. We propose a Visual Analytics solution for a decision support system to support the train operators in making an informed decision while providing access to the complex machine learning models. Different integrated, interactive views allow the train operator to explore the various impacts that a decision may have. Additionally, the user can compare various data-driven models which are structured by an experience-based model. We demonstrate a decision-making process in a use case highlighting how the different views are made use of by the train operator.

2019, Meschenmoser, Philipp, Buchmüller, Juri F., Keim, Daniel A.

Airspace route planning relies on many regulations and individual factors that can be hard to understand for audiences without advanced domain knowledge. This aspect is problematic if regulations are discussed in complex debates about changing air traffic distributions, affecting the broad public in negative and positive ways. To increase accessibility and transparency, we propose a regulation-oriented scheme of trajectory filters that includes a fully automated detection component for regulation deviations. The scheme further includes filters by daytime, custom areas, MTOM, and is part of a client-independent web prototype. In this publication, we specify details on individual filters and their inter- play (1st contribution), while putting a particular emphasis on the deviation detector (2nd contribution).

2021, Buchmüller, Juri F., Schlegel, Udo, Cakmak, Eren, Keim, Daniel A., Dimara, Evanthia

Compact visualization techniques such as dense pixel displays find application in displaying spatio-temporal datasets in a space-efficient way. While mostly focusing on feature development, the depiction of spatial distributions of the movers in these techniques is often traded against better scalability towards the number of moving objects. We propose SpatialRugs, a technique that can be applied to reintroduce spatial positions in such approaches by applying 2D colormaps to determine object locations and which enables users to follow spatio-temporal developments even in non-spatial representations. Geared towards collective movement datasets, we evaluate the applicability of several color maps and discuss limitations. To mitigate perceptional artifacts, we also present and evaluate a custom, time-aware color smoothing method.

2020, Meschenmoser, Philipp, Buchmüller, Juri F., Seebacher, Daniel, Wikelski, Martin, Keim, Daniel A.

Segmenting biologging time series of animals on multiple temporal scales is an essential step that requires complex techniques with careful parameterization and possibly cross-domain expertise. Yet, there is a lack of visual-interactive tools that strongly support such multi-scale segmentation. To close this gap, we present our MultiSegVA platform for interactively defining segmentation techniques and parameters on multiple temporal scales. MultiSegVA primarily contributes tailored, visual-interactive means and visual analytics paradigms for segmenting unlabeled time series on multiple scales. Further, to flexibly compose the multi-scale segmentation, the platform contributes a new visual query language that links a variety of segmentation techniques. To illustrate our approach, we present a domain-oriented set of segmentation techniques derived in collaboration with movement ecologists. We demonstrate the applicability and usefulness of MultiSegVA in two real-world use cases from movement ecology, related to behavior analysis after environment-aware segmentation, and after progressive clustering. Expert feedback from movement ecologists shows the effectiveness of tailored visual-interactive means and visual analytics paradigms at segmenting multi-scale data, enabling them to perform semantically meaningful analyses. A third use case demonstrates that MultiSegVA is generalizable to other domains.

2020, Kraus, Matthias, Miller, Matthias, Buchmüller, Juri F., Stein, Manuel, Weiler, Niklas, Keim, Daniel A., El-Assady, Mennatallah

Previous research has exposed the discrepancy between the subject of analysis (real world) and the actual data on which the analysis is performed (data world) as a critical weak spot in visual analysis pipelines. In this paper, we demonstrate how Virtual Reality (VR) can help to verify the correspondence of both worlds in the context of Information Visualization (InfoVis) and Visual Analytics (VA). Immersion allows the analyst to dive into the data world and collate it to familiar real-world scenarios. If the data world lacks crucial dimensions, then these are also missing in created virtual environments, which may draw the analyst’s attention to inconsistencies between the database and the subject of analysis. When situating VR in a generic visualization pipeline, we can confirm its basic equality compared to other mediums as well as possible benefits. To overcome the guarded stance of VR in InfoVis and VA, we present a structured analysis of arguments, exhibiting the circumstances that make VR a viable medium for visualizations. As a further contribution, we discuss how VR can aid in minimizing the gap between the data world and the real world and present a use case that demonstrates two solution approaches. Finally, we report on initial expert feedback attesting the applicability of our approach in a real-world scenario for crime scene investigation.

2020-03-27T08:53:09Z, Buchmüller, Juri F., Schlegel, Udo, Cakmak, Eren, Dimara, Evanthia, Keim, Daniel A.

Compact visual summaries of spatio-temporal movement data often strive to express accurate positions of movers. We present SpatialRugs, a technique to enhance the spatial awareness of movements in dense pixel visualizations. SpatialRugs apply 2D colormaps to visualize location mapped to a juxtaposed display. We explore the effect of various colormaps discussing perceptual limitations and introduce a custom color-smoothing method to mitigate distorted patterns of collective movement behavior.

2020, Cakmak, Eren, Schäfer, Hanna, Buchmüller, Juri F., Fuchs, Johannes, Schreck, Tobias, Jordan, Alex, Keim, Daniel A.

Domain experts for collective animal behavior analyze relationships between single animal movers and groups of animalsover time and space to detect emergent group properties. A common way to interpret this type of data is to visualize it as aspatio-temporal network. Collective behavior data sets are often large, and may hence result in dense and highly connectednode-link diagrams, resulting in issues of node-overlap and edge clutter. In this design study, in an iterative design process, wedeveloped glyphs as a design for seamlessly encoding relationships and movement characteristics of a single mover or clustersof movers. Based on these glyph designs, we developed a visual exploration prototype, MotionGlyphs, that supports domainexperts in interactively filtering, clustering, and animating spatio-temporal networks for collective animal behavior analysis. Bymeans of an expert evaluation, we show how MotionGlyphs supports important tasks and analysis goals of our domain experts,and we give evidence of the usefulness for analyzing spatio-temporal networks of collective animal behavior.

2019, Kraus, Matthias, Buchmüller, Juri F., Schweitzer, Daniel, Keim, Daniel A., Fuchs, Johannes

3D heightmaps can be considered as an extension of heatmaps using the third dimension to encode the respective value by height, often in addition to encoding it by color. In contrast to 2D heatmaps, 3D heightmaps allow a superposition without aggregation. However, they also have the general disadvantages of 3D visualizations, such as occlusion and perceptual distortion. Previous research has revealed various advantages of stereoscopic displays and virtual reality (VR) in the context of 3D visualizations, for example, concerning memorization, depth perception, and collaboration. In this paper, we present a novel technique to compare heightmaps in VR by introducing a multi-layer approach of stacked heightmaps. We demonstrate the applicability and usefulness of our method by means of a use case on comparative crime data analysis.