Feature Model for Information Visualization

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Feature Model for Information Visualization

Renan Vasconcelos Marcelo Schots Cláudia Werner

Systems Engineering and Computing – COPPE/UFRJ PO Box 68,511 – CEP 21945-970 – Rio de Janeiro, RJ, Brazil

{renanrv, schots, werner}@cos.ufrj.br

1. Introduction

Understanding different issues in a dynamic scenario involves dealing with a huge amount of data. Mechanisms are necessary in order to interpret and process data related to multiple situations. Awareness tools are key elements for managing incoming problems and providing means to feasible solutions.

Properly aiming the nature of data, visual abstractions can be combined with representation techniques for highlighting relevant aspects in a given context. Results analysis become possible through interaction alternatives that allow exploratory studies. Therefore, visual metaphors present an intuitive approach to support awareness [Schots et al. 2012].

Since a view can contain multiple visualization techniques, a technique selection perspective can be adopted to compose or choose a proper visualization. In software engineering, such concept is similar to the feature selection process in order to build a product line. Aiming at extracting the related visualization techniques, mapped to a feature model approach, a domain analysis has been carried out in order to identify desired characteristics in a visualization, structuring them into a feature model [Lee et al. 2002].

In order to choose the best visualization for a certain goal, its requirements can be expressed by the techniques it must offer or apply. For a given context, the feature selection process will provide the techniques set that the chosen view will have. In this sense, this report presents the identified features for an information visualization domain. Three categories were proposed to organize the large number of techniques, such as: Information Visualization, Presentation and Interaction.

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2 The visualization features categories were used to structure this report. Then, Section 2 presents the information visualization features category. Section 3 shows the presentation features category. Section 4 presents the interaction features category.

2. Information Visualization

 Type: Conceptual feature

 Definition: This feature comprises all functional features related to visualization techniques.

2.1. Focus + Context

 Type: Functional feature

 Definition: This feature integrates focus and context into a single display where all parts are concurrently visible and the focus is displayed seamlessly within its surrounding context [Cockburn et al. 2008].

2.1.1. Magic Lens

 Definition: This feature provides a transparent or semi-transparent user interface element which can be placed over items to change their appearance or their interactive behavior [Fox 1998]. Magic lenses allow to select a region of an object and to manipulate this area with specific operators. They can be moved like ordinary lenses and cover only a part of the object, which is shown with the effect applied [Waloszek 2004], also providing a natural way of supporting focus and context interfaces [Looser 2007].

 Constraints: Under evaluation  Image:

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3 2.1.2. Distortion

 Type: Functional feature  Tags: [Spatial Distortion]

 Definition: This feature comprises spatial distortion techniques that make the data interpretation possible, but also preserving the context during the exploration. A distortion algorithm increases the size of a region of interest while shrinking its surroundings [Shi et al. 2005]. A distorted view is created by applying a mathematical function, known as transformation, to an undistorted image. The transformation function defines how the original image is mapped to a distorted view [Stroe 1999].

 Rules: R - (Distortion) requires (Navigation) [Stroe 1999] 2.1.2.1. Fisheye View

 Definition: This feature diminishes or suppresses information that lies away from the focal area [Cockburn et al. 2008].

https://tulip.labri.fr/TulipDrupal/?q=node/351

2.1.2.2. Polyfocal Display  Type: Functional feature

 Definition: This feature applies polyfocal transformations, distorting the boundary of the representation. Such technique uses linear, hyperbolic or

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4 polynomial transformation functions and is described by two parameters: one is responsible for the value in the center of the focus and the other describes the rate of change of magnification with distance from the point of focus. Polyfocal displays can present multiple peaks [Stroe 1999].

[Stroe 1999]

2.2. Overview

 Definition: This feature provides a general context for understanding the data set; it paints a "picture" of the whole data entity that the information visualization represents. Patterns and themes in the data that may be helpful can often be seen only from a vantage point that comprises the whole view. From this perspective, major components and their relationships to one another are made evident [Craft and Cairns 2005].

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5

http://www.manuelm.org/blog/?p=175

2.3. Overview + Detail

 Definition: This feature is characterized by the simultaneous display of both an overview and detailed view of an information space, each in a distinct presentation space [Cockburn et al. 2008]. Although it relies on an overview approach, it is not considered a variation point of Overview because it also brings another different principle – the detail – to its proposal. Those two principles, the overview and the detail, produce a new visualization technique category, the Overview + Detail, which complements the Overview feature.  Rules: R_7 – (Overview + Detail) requires (Overview) [Cockburn et al. 2008]

2.3.1. Minimap

 Definition: A minimap comprises a scaled overview, centered in the current view area, but also showing its surroundings. The current view area is the component responsible for the details in the visualization [Oliveira 2011]. Due to display dimensions constraints, a minimap solution could be adopted while scrolling a visualization to present an overview of the content to the user [Roto et al. 2006].

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6  Constraints: Under evaluation

 Rules: R_1 – (Minimap) requires (Panning) [Roto et al. 2006]  Image:

http://clcsupport.com/phylogenymodule/current/Minimap.html

2.3.2. Thumbnail Overview  Type: Functional feature

 Definition: As the level of detail presented in the scroll trough increases, the scrollbar becomes a first-class overview window. Thumbnail document overviews blurs the boundary between scrollbar and overview for navigation [Cockburn et al. 2008].

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2.4. Overlap

 Definition: When a distribution tends to be sparse with areas of high density that are hard to see, overlapping items become common. This technique can be used toshow the item density [Fekete and Plaisant 2002].

2.4.1. Scatter Plot

 Definition: This feature displays values for two variables that belong to a data set. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis [Utts 2005].

 Constraints: Each data must contain a numeric tuple to the X and Y axes and a textual value to be mapped to a color or shape.

 Image:

http://en.wikipedia.org/wiki/Scatter_plot

2.4.2. Parallel Coordinates  Type: Functional feature

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8  Definition: This feature presents relations between coordinate axes, bringing them next to each other in an interactive way. The user can investigate how values are related to each other with special respect to two of the data dimensions [Hauser et al. 2002].

[Hauser et al. 2002]

2.4.3. Transparency

 Definition: This feature is useful when it can be varied interactively to reveal overlaps and density of overlapping items [Fekete and Plaisant 2002].

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9 2.4.4. Stereovision

 Definition: This feature requires a perspective projection that introduces occlusion and therefore overlaps. Like transparency, it is useful for transient inspections [Fekete and Plaisant 2002].

http://www.mathworks.com/help/vision/examples/stereo-vision.html

2.4.5. Flipping

 Definition: When the positions of the data items are preserved - i.e., when only changing colors or stacking order - flipping between views enables quick comparisons thanks to the retina persistency, suggesting an overlapping of images. Flipping shows the relationships between them while the sequential images are displayed [Fekete and Plaisant 2002].

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2.5. Hierarchical Visualization

 Definition: Hierarchies are information structures abstractions commonly used to represent complex structures [Chen 2006].

2.5.1. Treemap

 Type: Functional feature  Tags: [Space-filling layout]

 Definition: This feature maps hierarchical information to a rectangular 2D display in a space-filling manner, partitioning the display space into a collection of rectangular bounding boxes representing the tree structure [Johnson and Shneiderman 1991].

 Constraints: Only numerical data is allowed.  Image:

http://www.cs.umd.edu/hcil/treemap-history/

2.5.2. Cone Tree

 Definition: This technique provides an animated 3D visualization of hierarchical data structures. When a level in the hierarchy is expanded, its contents are arranged around the bottom of an inverted cone. It was intended to maximize effective use of available screen [Cockburn and McKenzie 2000].

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11  Constraints: Under evaluation

 Image:

http://www-graphics.stanford.edu/papers/webviz/htmlnosplit/

2.5.3. Radial

 Definition: This feature is suitable to show grouped information in the inner circles while presenting related detail information on the outer circles. It is complemented by appropriate interaction techniques like tooltips, drag & drop to adapt the order of the rings, filtering using clicks and details accessible via a popup menu [Keim et al. 2006].

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2.6. Clustering

 Definition: This feature aims at splitting a large data set into subgroups according to similarities measures in order to provide an easier way to analyze the data [Chen 2006].

http://graphlab.org/toolkits/clustering/

2.7. Animation

 Definition: This feature may help a viewer work through the logic behind an idea by showing the intermediate steps and transitions, or show how data collected over time changes. A moving image might offer a fresh perspective, or invite users to look deeper into the data presented [Steele and Iliinsky 2010] [Novais et al. 2013].

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http://kepler.nasa.gov/multimedia/animations/scienceconcepts/?ImageID=135

2.8. Layout

 Definition: This feature represents the spatial arrangement, organization or composition of multiple elements on a visualization [Hurlburt 1986].

http://edge.rit.edu/content/Resources/public/Help/Page%20Layout

2.8.1. 3D

 Definition: This feature provides a different perspective for a visualization layout. The content is presented in 3D to maximize effective use of available screen space and possibly enable visualization of a whole structure. A 3D layout uses depth to fill the screen with mode information [Robertson et al. 1991].  Constraints: Under evaluation

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14 [Trapp et al. 2013]

2.9. Details on Demand

 Definition: This feature is applied when an item or group is selected in order to get details when needed. Once a collection has been trimmed to a few dozen items, it should be easy to browse the details about the group or individual items [Shneiderman 1996].

2.9.1. Drill-Down

 Definition: This feature is related to the technique that reveals more details according to the user needs. A typical user interaction for locating a node consists of clicking the parent directory (or subtree) in which resides a node of interest [Shi et al. 2005]. It differs from the semantic zoom because it is associated to a hierarchy [Oliveira 2011].

 Constraints: Under evaluation

 Rules: R_2 – (Drill-Down OR Navigation) requires (Selection) [Shi et al. 2005] R_3 – (Drill-Down) requires (Hierarchical Visualization) [Oliveira 2011]  Image:

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15 [Shi et al. 2005]

2.9.2. Labeling

 Definition: Text labels are important to understand the context in which visualized data appear. Labeling each item cannot be done statically on a dense visualization, so dynamic techniques are advisable to be applied [Fekete and Plaisant 2002].

http://www.cs.umd.edu/hcil/VisuMillion/

2.9.2.1. Tooltip

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16  Definition: This feature provides access to help information and additional levels of documentation when requested. An interactive tooltip can also present navigation functionality within the associated data [Hudson et al. 2004].

http://br.freepik.com/psd-gratis/esfriar-passe-o-mouse-sobre-o-perfil-de-tooltip-psd_597285.htm

2.10. Binning

 Definition: This feature is usually applied when dealing with point-based data on a view. This approach overcomes the problem of overlapping, especially when the viewer zooms out of the visualization to view data at smaller scales. Data binning can be used to aggregate large point-based datasets into polygons to improve the navigation across all scales [Field 2012].

http://infosthetics.com/archives/2014/02/circular_binning_map_of_us_weather_conditi ons.html

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3. Presentation

 Definition: This feature comprises all functional features related to the presentation of different views.

3.1. Sequential

 Definition: This feature presents different views in a sequential order, where each view is displayed at a time.

Adapted from https://github.com/mbostock/d3/wiki/Gallery

3.2. Simultaneous

 Definition: This feature presents different views in a simultaneous way, where multiple views are displayed at the same time.

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4. Interaction

 Definition: This feature comprises all functional features related to the user interaction on a view.

4.1. Filtering

 Definition: Since data sets can be very large, it is convenient and necessary to visualize/emphasize only what is relevant in a certain context. In these situations, information filtering must be applied [Oliveira 2011].

4.1.1. Mode

 Definition: This feature comprises all functional features related to the interaction mode on a view.

4.1.1.1. Dynamic

 Definition: This feature presents a dynamic interaction available to be used on a view. A dynamic interaction allows the user to change parameters and alter the displayed result on the fly.

4.1.1.2. Static

 Definition: This feature presents a static interaction on a view. A static interaction shows the result of an applied interaction on a view. In this situation, the user cannot use that interaction technique to change the displayed result.

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19 4.1.2. Method

 Definition: This feature comprises all techniques related to the interaction method on a view.

4.1.2.1. Highlighting / Mitigation  Type: Functional feature

 Definition: This feature comprises highlighting techniques that can be used to draw attention to certain items in a field of thousands of items [Shneiderman 1996]. Mitigation is related to the opposite idea of highlighting, making surrounding items less evident, so that the main elements could be highlighted [Oliveira 2011]. A related principle that must be addressed is brushing, which is responsible for selecting a subset of the data items in order to highlight this subset, but it can also be done to delete it from the view or to de-emphasize it, if the user wants to focus on the other items [Voigt 2002].

Adapted from [Voigt 2002]

4.1.2.2. Inclusion / Removal  Type: Functional feature

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20  Definition: This feature comprises techniques that apply the filtering process by directly including relevant items on a view or by removing the non-important ones from it [Oliveira 2011].

[Carneiro et al. 2010]

4.1.2.3.

Collapse / Expand  Type: Functional feature

 Definition: This feature allows the user to obtain a high or low level view of the displayed collection, collapsing (also known as “contracting”) or expanding, respectively, a visualization [Novais et al. 2013] [Holmes and Walker 2007].  Constraints: Under evaluation

 Image:

Created with d3.js1

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21 4.1.2.4. Sampling

 Definition: Every data set is a sample of some real phenomena and sampling is already there, embedded in the data [Bertini 2011]. However resources must be applied to use this technique in order to reveal the underlying characteristics of data and what is the amount of sampling that should be employed to obtain an adequate visual representation [Bertini 2004].

[Bertini 2004]

4.1.2.5. Tuning / Tweaking  Type: Functional feature

 Definition: With tweaking and tuning it is possible to change different parameters in order to make an intended picture stand from the screen. It gets things like changing transparency, size, colors, positions, bending curves, and all the rest [Bertini 2011].

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22

http://blog.ouseful.info/2011/07/07/visualising-twitter-friend-connections-using-gephi-an-example-using-wireduk-friends-network/

4.1.2.6. Segmentation

 Definition: Segmentation according to some parameter can be used to analyze data. Much knowledge can be extracted when comparing segments of data. Analyzing one segment at a time can provide more options and offer a new perspective [Bertini 2011].

http://www.kaushik.net/avinash/google-analytics-visitor-segmentation-users-sequences-cohorts/

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4.2. Panning

 Definition: This feature comprises techniques related to an interaction that performs a smooth movement of camera across scene or the scene moves and the camera stays still [Stasko 2005]. Panning is an interaction through constant scale [Oliveira 2011].

4.2.1. Drag and Drop

 Definition: This feature is applied when an interaction is intended to grab an element and drag it to another location [W3Schools 2014]. In panoramic views, it allows moving an object into and out of the focus area [Oliveira 2011].

http://www.ist.co.uk/motif/books/vol6A/ch-22.fm.html

4.3. Sorting

 Definition: This feature can be used to organize the amount of data displayed in the view canvas [Novais et al. 2013].

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24

http://waack.org/2012/12/31/sonification-of-search-algorithms/gnome-sort-algorithm-visualization-sonification-audification/

4.4. Linking

 Definition: This feature is responsible for showing how an element, or set of elements, behaves in each of the views. This can be accomplished by highlighting these points in some fashion [NIST/SEMATECH 2004]. Interactive changes made in one visualization are automatically reflected in the other visualizations. Note that connecting multiple visualizations through interactive linking provides more information than considering the component visualizations independently [Keim 2002]. Linking should not be confused with the existence of hiperlinks in a view.

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4.5. Browsing

 Definition: This feature is an interaction technique that supports exploratory searches within a given subset without any prior knowledge. Browsing is a powerful and required facility in many situations. Of course, when offered as the only access mechanism in large libraries, browsing has its limitations. On the other hand, when augmented with filters and orientation facilities, and coupled with additional retrieval modes, browsing becomes a very effective access mode [Constantopoulos et al. 1995].

http://online.uark.edu/support/tutorials/student/navigation_in_Bb.html

4.5.1.

Navigation

 Definition: This feature is an interaction technique that helps to go through the data and the different views [Novais et al. 2013]. Also known as direct browsing [Ye et al. 2000] or implicit querying [Constantopoulos et al. 1995], it is applied through navigational commands in the browsing mode.

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26  Image:

http://www.1wordtut.com/2013/02/navigating-in-document-in-word-2010-free-tutorial.html

4.5.2.

Querying

 Definition: This feature helps, through queries, to organize or restrict the amount of data displayed in a view [Novais et al. 2013]. Also called keyword-based browsing [Ye et al. 2000], an explicit query involves an arbitrary predicate explicitly formulated in a query language or through an appropriate form interface [Constantopoulos et al. 1995]. Dynamic queries can continuously update the visualized data that is filtered from the data source, such as a database. They may work instantly within milliseconds as users adjust sliders or select buttons to form simple queries or to find patterns or exceptions; the dynamic–query approach thus applies the principles of direct manipulation to the database [Shneiderman 1994]. Usually, as the result of querying, filtering alternatives are applied to the visualization.

 Rules: R_4 - (Querying) requires (Filtering) [Shneiderman 1994]  Image:

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http://vsdlc3.blogspot.com.br/

4.6. Selection

 Definition: This feature is related to a very common mechanism of interaction, where the user can strictly choose an option or focus on an item [Novais et al. 2013].

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4.7. Aggregation

 Definition: This feature can be considered as the opposite of sampling.

Aggregation can be used to obtain a more complete visualization of a dataset

[Novais et al. 2013] [Bertini 2011].  Constraints: Under evaluation  Image:

Created with d3.js2

4.8. Rotate

 Definition: This feature allows the user to interact by rotating an object on a view or by rotating the camera [Novais et al. 2013].

 Rules: R_5 - (Rotate) requires (Selection)  Image:

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http://www.geom.uiuc.edu/projects/visualization/using.html

4.9. Zooming

 Definition: This feature comprises the interaction techniques related to dynamically increasing or reducing the size of a visual element [Diehl 2007].  Rules: R_6 - (Zooming AND Semantic) requires (Details on Demand) [Buering

et al. 2006]

4.9.1. Geometric

 Definition: This feature is responsible for enlarging objects while zooming in and shrinking them while zooming out [Buering et al. 2006].

http://iopscience.iop.org/1367-2630/10/12/125006/fulltext/

4.9.2. Semantic

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30  Definition: This feature is applied through the interaction that shows different visual representations to information items, according to the available space [Buering et al. 2006].

 Rules: R_6 - (Zooming AND Semantic) requires (Details on Demand) [Buering et al. 2006]

 Image:

[Su 2010]

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