The State of the Art in Map‐Like Visualization

Hogräfer, Marius; Heitzler, Magnus; Schulz, Hans-Jörg

doi:10.1111/cgf.14031

Cited by 39 publications

(25 citation statements)

References 203 publications

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“…Version #4: Representation-driven-We eventually decided to code visualization techniques according to how they balance their visual representations at the tension between (i) explicitly showing all possible information in a geospatial network, that is all links, all nodes, all geographic information and places of interest, and (ii) managing visual clutter and information overload to provide for efficient task-oriented visual representation. We found our design space, dimensions, and classifications to best capture the trade-offs required in designing geospatial network visualizations and to provide a conceptual framework perhaps similar to the design space described by space-time cubes [BDA*17] or map-like visualizations [HHS20]. The complete rationale is given in Section 4.3.…”

Section: Creating a Design Spacementioning

confidence: 99%

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Visualizing and Interacting with Geospatial Networks: A Survey and Design Space

Schöttler

Yang

Pfister

et al. 2021

Computer Graphics Forum

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This paper surveys visualization and interaction techniques for geospatial networks from a total of 95 papers. Geospatial networks are graphs where nodes and links can be associated with geographic locations. Examples can include social networks, trade and migration, as well as traffic and transport networks. Visualizing geospatial networks poses numerous challenges around the integration of both network and geographical information as well as additional information such as node and link attributes, time and uncertainty. Our overview analyses existing techniques along four dimensions: (i) the representation of geographical information, (ii) the representation of network information, (iii) the visual integration of both and (iv) the use of interaction. These four dimensions allow us to discuss techniques with respect to the trade-offs they make between showing information across all these dimensions and how they solve the problem of showing as much information as necessary while maintaining readability of the visualization. https:// geonetworks.github.io.

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Section: Creating a Design Spacementioning

confidence: 99%

“…A second advantage of mapped techniques is that people are familiar with geographic data being displayed on maps. Maps have been shown to have cognitive benefits when interpreting geographic data [HHS20].…”

Section: D1-geo: Mappedmentioning

confidence: 99%

Visualizing and Interacting with Geospatial Networks: A Survey and Design Space

Schöttler

Yang

Pfister

et al. 2021

Computer Graphics Forum

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“…A classic example is the TableLens [61] and variants of it [36,49]. In the future, it would also be interesting to explore the applicability of RMCs in the context of irregular arrangements, for example, if and how RMCs can be applied to maps or map-like visualizations [32].…”

Section: Facets Of Responsivenessmentioning

confidence: 99%

Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs

Horak

Berger

Schumann

et al. 2021

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Responsive matrix cells are a focus+context approach that provides details for a multivariate graph via embedded visualizations in a matrix representation and allows analysts to go from the overview in the matrix to details as well as editing within the cells. c b Abstract-Matrix visualizations are a useful tool to provide a general overview of a graph's structure. For multivariate graphs, a remaining challenge is to cope with the attributes that are associated with nodes and edges. Addressing this challenge, we propose responsive matrix cells as a focus+context approach for embedding additional interactive views into a matrix. Responsive matrix cells are local zoomable regions of interest that provide auxiliary data exploration and editing facilities for multivariate graphs. They behave responsively by adapting their visual contents to the cell location, the available display space, and the user task. Responsive matrix cells enable users to reveal details about the graph, compare node and edge attributes, and edit data values directly in a matrix without resorting to external views or tools. We report the general design considerations for responsive matrix cells covering the visual and interactive means necessary to support a seamless data exploration and editing. Responsive matrix cells have been implemented in a web-based prototype based on which we demonstrate the utility of our approach. We describe a walk-through for the use case of analyzing a graph of soccer players and report on insights from a preliminary user feedback session.

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“…Researchers have built many map-like visualization works around spatialization [15]. Administrative maps with polygons as map units are a common map form in daily life.…”

Section: Related Workmentioning

confidence: 99%

“…Persistence in Function 14 is introduced for noise amplitude reduction. Finally, weighted mixing of the noise data FractalNoise and the base terrain data BaseHeight is performed by Function (15) to obtain the final terrain data result Height and make the noisy terrain as shown in Figure 14. In Function (15), NR is the weight of noise in the final terrain result by which the noise proportion can be controlled.…”

Section: Multi-scale Expression Of Terrainmentioning

confidence: 99%

A Multi-Scale Virtual Terrain for Hierarchically Structured Non-Location Data

Rui

Zhu

et al. 2021

IJGI

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Metaphor are commonly used rhetorical devices in linguistics. Among the various types, spatial metaphors are relatively common because of their intuitive and sensible nature. There are also many studies that use spatial metaphors to express non-location data in the field of visualization. For instance, some virtual terrains can be built based on computer technologies and visualization methods. In virtual terrains, the original abstract data can obtain specific positions, shapes, colors, etc. and people’s visual and image thinking can play a role. In addition, the theories and methods used in the space field could be applied to help people observe and analyze abstract data. However, current research has limited the use of these space theories and methods. For instance, many existing map theories and methods are not well combined. In addition, it is difficult to fully display data in virtual terrains, such as showing the structure and relationship at the same time. Facing the above problems, this study takes hierarchical data as the research object and expresses both the data structure and relationship from a spatial perspective. First, the conversion from high-dimensional non-location data to two-dimensional discrete points is achieved by a dimensionality reduction algorithm to reflect the data relationship. Based on this, kernel density estimation interpolation and fractal noise algorithms are used to construct terrain features in the virtual terrains. Under the control of the kernel density search radius and noise proportion, a multi-scale terrain model is built with the help of level of detail (LOD) technology to express the hierarchical structure and support the multi-scale analysis of data. Finally, experiments with actual data are carried out to verify the proposed method.

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The State of the Art in Map‐Like Visualization

Cited by 39 publications

References 203 publications

Visualizing and Interacting with Geospatial Networks: A Survey and Design Space

Visualizing and Interacting with Geospatial Networks: A Survey and Design Space

Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs

A Multi-Scale Virtual Terrain for Hierarchically Structured Non-Location Data

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