A Characterization of Data Exchange between Visual Analytics Tools
International Conference on Information Visualization (IV) <24, 2020, online>
Over the past years, the visualization of large andcomplex data sets brought up various Visual Analytics (VA)tools in order to solve domain-specific tasks. These VA toolsare typically implemented as individual software componentsin data-flow-oriented models, meaning that data is transferredfrom one component to the next. While most VA frameworksrely on a monolithic architecture with features for the integration of specialized analysis methods, we consider a loosecoupling of independent applications, where autonomous VAtools are used in predefined analysis sequences. To this end,we provide a characterization of the data exchange processamong individual VA tools in the form of a taxonomy. Thistaxonomy can be used as a checklist to identify characteristicsand improve the data flow of one’s own multi-tool VA setup.For this purpose, we conducted a systematic investigation of theindividual aspects of data exchange that are commonly foundacross different usage scenarios. We apply our taxonomy tothree existing multi-tool frameworks, the open-source libraryReVize, the toolchain editor AnyProc, and the visualizationand monitoring framework Plant@Hand3D.
A Layered Approach to Lightweight Toolchaining in Visual Analytics
The 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019). Proceedings
International Joint Conference on Computer Vision and Computer Graphics Theory and Applications (VISIGRAPP) <14, 2019, Prague, Czech Republic>
Communications in Computer and Information Science, 1182
The ongoing proliferation and differentiation of Visual Analytics to various application domains and usage scenarios has also resulted in a fragmentation of the software landscape for data analysis. Highly specialized tools are available that focus on one particular analysis task in one particular application domain. The interoperability of these tools, which are often research prototypes without support or proper documentation, is hardly ever considered outside of the toolset they were originally intended to work with. To nevertheless use and reuse them in other settings and together with other tools, so as to realize novel analysis procedures by using them in concert, we propose an approach for loosely coupling individual visual analytics tools together into toolchains. Our approach differs from existing such mechanisms by being lightweight in realizing a pairwise coupling between tools without a central broker, and by being layered into different aspects of such a coupling: the usage flow, the data flow, and the control flow. We present a model of this approach and showcase its usefulness with three different usage examples, each focusing on one of the layers.
Lightweight Coordination of Multiple Independent Visual Analytics Tools
IVAPP 2019. Proceedings
International Conference on Information Visualization Theory and Applications (IVAPP) <10, 2019, Prague, Czech Republic>
With the advancement of Visual Analytics (VA) and its spread into various application fields comes along a specialization of methods and tools. This adds complexity and requires extra effort when devising domain-dependent VA solutions, as for every new domain question a new specialized tool or framework must be developed. In this paper, we investigate the possibility of using and re-using existing tools – domain-dependent and general-purpose – by loosely coupling them into specialized VA tool ensembles as needed. We call such coupling among independent tools lightweight coordination, as it is minimally-invasive, pair-wise, and opportunistic in utilizing whichever interface a VA tool offers. We propose the use of lightweight coordination for managing the workflow, the data flow, and the control flow among VA tools, and we show how it can be supported with suitable setups of the multiple tool UIs involved. This concept of lightweight coordination is exemplified with a health care scenario, where an ensemble of independent VA tools is used in a concerted way to pursue the visual analysis of a patient’s troublesome vital data.
The Human User in Progressive Visual Analytics
EuroVis 2019. Eurographics / IEEE VGTC Conference on Visualization 2019: Short Papers
Eurographics / IEEE VGTC Conference on Visualization (EuroVis) <21, 2019, Porto, Portugal>
The amount of generated and analyzed data is ever increasing, and processing such large data sets can take too long in situations where time-to-decision or fluid data exploration are critical. Progressive visual analytics (PVA) has recently emerged as a potential solution that allows users to analyze intermediary results during the computation without waiting for the computation to complete. However, there has been limited consideration on how these techniques impact the user. Based on discussions from a Dagstuhl seminar held in October 2018, this paper characterizes PVA users by their common roles, their main tasks, and their distinct focus of analysis. It further discusses cognitive biases that play a particular role in PVA. This work will help PVA visualization designers in devising systems that are tailored for their specific target users and their characteristics.
Vision, Modeling, and Visualization
University of Rostock
Vision, Modeling, and Visualization (VMV) <24, 2019, Rostock, Germany>
Characterizing Guidance in Visual Analytics
IEEE Transactions on Visualization and Computer Graphics
IEEE Conference on Visual Analytics Science and Technology (VAST) <11, 2016, Baltimore, MD, USA>
Visual analytics (VA) is typically applied in scenarios where complex data has to be analyzed. Unfortunately, there is a natural correlation between the complexity of the data and the complexity of the tools to study them. An adverse effect of complicated tools is that analytical goals are more difficult to reach. Therefore, it makes sense to consider methods that guide or assist users in the visual analysis process. Several such methods already exist in the literature, yet we are lacking a general model that facilitates in-depth reasoning about guidance. We establish such a model by extending van Wijk's model of visualization with the fundamental components of guidance. Guidance is defined as a process that gradually narrows the gap that hinders effective continuation of the data analysis. We describe diverse inputs based on which guidance can be generated and discuss different degrees of guidance and means to incorporate guidance into VA tools. We use existing guidance approaches from the literature to illustrate the various aspects of our model. As a conclusion, we identify research challenges and suggest directions for future studies. With our work we take a necessary step to pave the way to a systematic development of guidance techniques that effectively support users in the context of VA.
An Enhanced Visualization Process Model for Incremental Visualization
IEEE Transactions on Visualization and Computer Graphics
With today's technical possibilities, a stable visualization scenario can no longer be assumed as a matter of course, as underlying data and targeted display setup are much more in flux than in traditional scenarios. Incremental visualization approaches are a means to address this challenge, as they permit the user to interact with, steer, and change the visualization at intermediate time points and not just after it has been completed. In this paper, we put forward a model for incremental visualizations that is based on the established Data State Reference Model, but extends it in ways to also represent partitioned data and visualization operators to facilitate intermediate visualization updates. In combination, partitioned data and operators can be used independently and in combination to strike tailored compromises between output quality, shown data quantity, and responsiveness-i.e., frame rates. We showcase the new expressive power of this model by discussing the opportunities and challenges of incremental visualization in general and its usage in a real world scenario in particular.
A Survey of Multi-faceted Graph Visualization
Eurographics Conference on Visualization (EuroVis) 2015 - STARs
Eurographics Conference on Visualization (EuroVis) <17, 2015, Cagliari, Sardinia, Italy>
Graph visualization is an important field in information visualization that is centered on the graphical display of graph-structured data. Yet real world data is rarely just graph-structured, but instead exhibits multiple facets, such as multivariate attributes, or spatial and temporal frames of reference. In an effort to display different facets of a graph, such a wealth of visualization techniques has been developed in the past that current surveys focus on a single additional facet only in order to enumerate and classify them. This report builds on existing graph visualization surveys for the four common facets of partitions, attributes, time, and space. It contributes a generic high-level categorization of faceted graph visualization that subsumes the existing classifications, which can be understood as facet-specific refinements of the resulting categories. Furthermore, it extends beyond existing surveys by applying the same categorization to graph visualizations with multiple facets. For each of the introduced categories and considered facets, this overview provides visualization examples to illustrate instances of their realization.
Exploring Hierarchical Visualization Designs Using Phylogenetic Trees
Visualization and Data Analysis 2015
IS&T/SPIE Conference on Visualization and Data Analysis (VDA) <15, 2015, San Francisco, CA, USA>
Ongoing research on information visualization has produced an ever-increasing number of visualization designs. Despite this activity, limited progress has been made in categorizing this large number of information visualizations. This makes understanding their common design features challenging, and obscures the yet unexplored areas of novel designs. With this work, we provide categorization from an evolutionary perspective, leveraging a computational model to represent evolutionary processes, the phylogenetic tree. The result - a phylogenetic tree of a design corpus of hierarchical visualizations - enables better understanding of the various design features of hierarchical information visualizations, and further illuminates the space in which the visualizations lie, through support for interactive clustering and novel design suggestions. We demonstrate these benefits with our software system, where a corpus of two-dimensional hierarchical visualization designs is constructed into a phylogenetic tree. This software system supports visual interactive clustering and suggesting for novel designs; the latter capacity is also demonstrated via collaboration with an artist who sketched new designs using our system.
Interactive Presentation of Geo-Spatial Climate Data in Multi-Display Environments
ISPRS International Journal of Geo-Information
The visual analysis of complex geo-spatial data is a challenging task. Typically, different views are used to communicate different aspects. With changing topics of interest, however, novel views are required. This leads to dynamically changing presentations of multiple views. This paper introduces a novel approach to support such scenarios. It allows for a spontaneous incorporation of views from different sources and to automatically layout these views in a multi-display environment. Furthermore, we introduce an enhanced undo/redo mechanism for this setting, which records user interactions and, in this way, enables swift reconfigurations of displayed views. Hence, users can fluently switch the focus of visual analysis without extensive manual interactions. We demonstrate our approach by the particular use case of discussing geo-spatial climate data.
Preset-based Generation and Exploration of Visualization Designs
Journal of Visual Languages & Computing
Generating the "right" visual representation for the data and task at hand remains a standing challenge in visualization research and practice. A variety of different approaches to produce visual representations have been proposed in the past, including such noteworthy instances as visualization by example and visualization by analogy. With this paper, we add a new twist to creating visual representations by proposing away to construct new visualization designs by blending together a number of existing visual representations, called presets. We embed this novel blending approach in suitable visual interfaces, such as a gridded canvas to be used by the casual user in the style of a palette for mixing colors, or a range of sliders to be used by the expert user in the style of a studio mixer for audio tracks. These can be employed for rapid prototyping of a specific visual representation, as well as to explore the overall design space of visual representations captured by our approach. We showcase our preset-based blending and its interfaces with examples of the design of 2D tree visualizations and product plots.
Proceedings of the International Summer School on Visual Computing 2015
International Summer School on Visual Computing <1, 2015, Rostock, Germany>
The research field of Visual Computing encompasses everything graphical in computer science - from the synthesis and processing of graphical content to its human consumption. This broad spectrum includes multiple other fields that constitute research disciplines in their own right, such as perception, visualization, multimedia, virtual and augmented reality, as well as human-computer interaction. The first International Summer School on Visual Computing held from August 17-21, 2015 at the Fraunhofer IGD Rostock, Germany aimed to give an overview of this broad field to graduate students from Rostock, Germany, and abroad. A week-long program of lectures and research talks by invited speakers introduced participating students into the subjects of visual perception and cognition, eye tracking, raster image databases, multimedia retrieval, computer vision, human-computer-interaction, mobile and wearable computing, and visual analytics. Each afternoon, the participating students had the opportunity to present their own research in posters and talks. Sessions with helpful tips and tricks on how to go about PhD level research, writing, and presentation, as well as an open lab tour rounded off the summer school program.
Review: Visual Analytics of Climate Networks
Nonlinear Processes in Geophysics
Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.
Towards a Contextualized Visual Analysis of Heterogeneous Manufacturing Data
Advances in Visual Computing. 9th International Symposium, ISVC 2013
International Symposium on Visual Computing (ISVC) <9, 2013, Rethymnon, Crete, Greece>
Visual analysis spanning multiple data sources usually requires the integration of multiple specialized applications to handle their heterogeneity. This is also true in manufacturing, where data about orders, personnel, workloads, maintenance, etc. must be analyzed together to make well-founded management decisions. Yet, the orchestration of multiple data sources and applications poses challenges to the software infrastructure and to the analyst. We present a three-tiered approach to cope with these challenges. In a first step, we establish a domaindependent workflow as the mental model of the analyst. Based on the novel concept of contextualization, we then align the different applications with this model for their meaningful integration. In a third step, we incorporate the data according to its use in the aligned applications by means of a service-based architecture. By starting the integration on the user level, we are able to pragmatically target and streamline the required integration to a degree that is technically achievable and interactively manageable. We exemplify our approach with the Plant@Hand system for integrating manufacturing data and applications.