Managing Spatial Selections With Contextual Snapshots

2007

ABSTRACT There is presently a variety of methods by which to create visualizations, and many of these require a great deal of manual intervention. Even with those methods by which it is easy to create a single visual representation, understanding the range of possible visual representations and exploring amongst them is difficult.

2005

Exploratory visualization enables the user to test scenarios and investigate possibilities. Through an exploration, the user may change various parameter values of a visualization system that in turn alters the appearance of the visual result. For example, the changes made may update what information is being displayed, the quantity or resolution of the information, the type of the display (say) from scatter plot to line-graph. Furthermore, the user may generate additional windows that contain the visual result of the new parameters so they can compare different ideas side-by-side (these multiple views may persist such that the user can compare previous incarnations). Commonly these windows are linked together to allow further investigation and discovery, such as selection by brushing or combined navigation. There are many challenges, such as linking multiple views with different data, initializing the different views, indicating to the user how the different views are linked. This chapter provides a review of current multiple linked-view tools, methodologies and models, discusses related challenges and ideas, and provides some rudiments for coordination within a geovisualization context. The types and uses of coordination for exploratory visualization are varied and diverse, these ideas are underused in geovisualization and exploratory visualization in general. Thus, further research needs to occur to develop specific geovisualization reference models and extensible systems that incorporate the rich variety of possible coordination exploration ideas.

Existing map-based visualizations of scientific datasets support a small number of tasks. They do not allow users to visually inspect properties and contexts in scientific datasets and focus only on showing locations in space and time. This paper describes a prototype that provides a better support for visual analyses of scientific contexts by means of additional representations and richer interactions with scientific data.

Information Visualization, 2008

Spatiotemporal databases provide effective means to represent, manage and query information evolving over time. However, the visualization of record sets that result from spatiotemporal queries through traditional visualization techniques can be of difficult interpretation or may lack the ability to meaningfully display several instants at the same time. We propose a Temporal Focus + Context visualization model to overcome issues from such techniques resorting to concepts from Information Visualization. In this model, Focus + Context is applied to time rather than, as more typically, to attributes or space, and allows large amounts of data from distinct periods of time and from several record sets to be compressed onto one. Underlying the proposed visualization technique is the calculation of a temporal degree of interest (TDOI) for each record driven by specific analysis, exploration or presentation goals and based on the record valid time attribute, as well as on user-defined temp...

2012 IEEE Conference on Visual Analytics Science and Technology (VAST), 2012

Visualizations embody design choices about data access, data transformation, visual representation, and interaction. To interpret a static visualization, a person must identify the correspondences between the visual representation and the underlying data. These correspondences become moving targets when a visualization is dynamic. Dynamics may be introduced in a visualization at any point in the analysis and visualization process. For example, the data itself may be streaming, shifting subsets may be selected, visual representations may be animated, and interaction may modify presentation. In this paper, we focus on the impact of dynamic data. We present a taxonomy and conceptual framework for understanding how data changes influence the interpretability of visual representations. Visualization techniques are organized into categories at various levels of abstraction. The salient characteristics of each category and task suitability are discussed through examples from the scientific literature and popular practices. Examining the implications of dynamically updating visualizations warrants attention because it directly impacts the interpretability (and thus utility) of visualizations. The taxonomy presented provides a reference point for further exploration of dynamic data visualization techniques.

In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of elements from a dynamic multidimensional data set on a 2D grid as the set changes. Here, we introduce a novel layout that uses pairwise similarity from grid neighbors, as defined in incBoard, to reposition elements on the visual space, free from constraints imposed by the grid. The board continues to be updated and can be displayed alongside the new space. As similar items are placed together, while dissimilar neighbors are moved apart, it supports users in the identification of clusters and subsets of related elements. Densely populated areas identified in the incSpace can be efficiently explored with the corresponding incBoard visualization, which is not susceptible to occlusion. The solution remains inherently incremental and maintains a coherent disposition of elements, even for fully renewed sets. The algorithm considers relative positions for the initial placement of elements, and raw dissimilarity to fine tune the visualization. It has low computational cost, with complexity depending only on the size of the currently viewed subset, V. Thus, a data set of size N can be sequentially displayed in O(N) time, reaching O(N 2 ) only if the complete set is simultaneously displayed.

2002

Information visualization, aided by ever more accessible computational resources, continues to grow in popularity and significance. The capability to generate complex imagery by computer is often necessary but not always sufficient to gain the desired insight. The success of a visual representation in a given context may be affected by many variables, not the least of which is the individual user's experience. Even if a precise relationship could be found between context and "best" visual representation, the complete articulation of a context is practically impossible. In other fields, this is known as sensitive dependence to initial conditions. A more feasible alternative is to begin with an incomplete articulation of a context and allow the user to interactively develop and refine it. Although most computer interfaces for information visualization tools are predominantly verbal, a predominantly visual interface can have significant advantages. Such an interface allows users to avoid the usual translations between visual and verbal modes and it removes users' need for a specialized visualization vocabulary. A visual interface can also shift the focus of the visualization process from the data towards the user. These ideas are discussed in the context of a prototype tool, the design of which is illustrated with an example, and the evaluation of which has provided many positive results.

Handbook of Data Visualization, 2008

The basic problem in visualization still is the physical limitation of the -D presen-tation space of paper and computer screens. There are basically four approaches to addressing this problem and to overcoming the restrictions of two-dimensionality: . Create a virtual reality ...

… and Environments, 2001. …, 2001

This poper describes visuolisation tools to support the tusk ofselecting one object from o collection of many on the basis of its attribute vulues. For this frequently encountered task we identth o set of tools appropriate to 4 spectrum of collection sizes extendingfrom hundreds of ...

IEEE transactions on visualization and computer graphics, 2018

We present a direct manipulation technique that allows material scientists to interactively highlight relevant parameterized simulation instances located in dimensionally reduced spaces, enabling a user-defined understanding of a continuous parameter space. Our goals are two-fold: first, to build a user-directed intuition of dimensionally reduced data, and second, to provide a mechanism for creatively exploring parameter relationships in parameterized simulation sets, called ensembles. We start by visualizing ensemble data instances in dimensionally reduced scatter plots. To understand these abstract views, we employ user-defined virtual data instances that, through direct manipulation, search an ensemble for similar instances. Users can create multiple of these direct manipulation queries to visually annotate the spaces with sets of highlighted ensemble data instances. User-defined goals are therefore translated into custom illustrations that are projected onto the dimensionally re...

Multimedia Tools and Applications, 2010

In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of elements from a dynamic multidimensional data set on a 2D grid as the set changes. Here, we introduce a novel layout that uses pairwise similarity from grid neighbors, as defined in incBoard, to reposition elements on the visual space, free from constraints imposed by the grid. The board continues to be updated and can be displayed alongside the new space. As similar items are placed together, while dissimilar neighbors are moved apart, it supports users in the identification of clusters and subsets of related elements. Densely populated areas identified in the incSpace can be efficiently explored with the corresponding incBoard visualization, which is not susceptible to occlusion. The solution remains inherently incremental and maintains a coherent disposition of elements, even for fully renewed sets. The algorithm considers relative positions for the initial placement of elements, and raw dissimilarity to fine tune the visualization. It has low computational cost, with complexity depending only on the size of the currently viewed subset, V. Thus, a data set of size N can be sequentially displayed in O(N) time, reaching O(N 2) only if the complete set is simultaneously displayed.

Fifth International Conference on Coordinated and Multiple Views in Exploratory Visualization (CMV 2007), 2007

The area of Coordinated and Multiple Views has been steadily developing and maturing over the past fifteen years. Some may say that it is a 'solved problem', while others argue that we are only just scratching the surface of the subject. Considering merely the CMV conference series, it is clear to see that in the early years researchers were concerned with models and techniques, while in latter years authors presented more work on how to apply these ideas to different domains. It is our view that there is still much research to be done, but the subject is changing and developing as a tool for Visual Analytics. This paper provides the 'state of the art' of CMV, it describes areas that should be developed further and looks at what the future may hold for Coordinated and Multiple Views.

2008 12th International Conference Information Visualisation, 2008

Empirical comparisons and categorizations of information visualization tools lack important considerations: the former undervalue the need for a theoretical background, and the latter tend to have too much distance from the user because they do not consider definite user tasks. Therefore, our work combines these approaches and presents the results of both a qualitative evaluation and a recently published categorization. We focus on the visualization of temporal data and reveal that current tools realize only a small part of the visualization possibilities in this field. Abstract Abstract Abstract/Spatial Reference Spatial Spatial data can be explored.

IEEE Computer Graphics and Applications, 2000

S cientific visualization involves communication of simulated or measured data to a human user. The growing efficiency of today's high-performance computers enables simulation of physical phenomena with a high temporal resolution and for a long time span. Consequently, visualization systems require efficient interaction techniques to navigate in the visualized timevarying data. Today, scientists use virtual reality to analyze visualizations of complex spatiotemporal phenomena, enabling an interactive, immersive work process. For timevarying data, scientists often use animated visualizations because they correspond to the natural perception of time. Navigating in an animated visualization requires interfaces to control the flow of time. To accomplish this, most VR-based visualization systems provide the user with linear time sliders, along with VCR controls such as play, stop, fast forward, and reverse. Besides the known drawbacks of slider elements, these interaction techniques ignore that spatial phenomena are the focus of interest in VR-based scientific visualization. Slider controls are useful for time-centered browsing tasks (for example, "What happens after 1.5 seconds?"), but they're only an intermediary to investigate the temporal progression of a visualized phenomenon.

2005

: VisTrails Visualization Spreadsheet. This ensemble shows the surface salinity variation at the mouth of the Columbia River over the period of a day. The green regions represent the fresh-water discharge of the river into the ocean. A single vistrail specification is used to construct this ensemble. Each cell corresponds to an instance of this specification executed using a different timestamp value.