CONSTRUCTING VISUALIZATIONS WITH INFOVIS TOOLS

An Evaluation from a User Perspective

Kostas Pantazos and Soren Lauesen

Software Development Group, IT-University Of Copenhagen, Rued Langgaards Vej 7, Copenhagen, Denmark

Keywords:

Information Visualization, Tools, Toolkits, Evaluation, User Perspective.

Abstract:

Several information visualization toolkits and tools have been developed to facilitate users work. However,

evaluation studies for these toolkits and tools from a user perspective have been overlooked. In this paper, we

evaluate 13 information visualization toolkits and tools developed in the last 10 years from a user perspective.

For each user type (novice, savvy and expert), we investigated the toolkits and tools using 5 dimensions.

This study shows that tools for savvy users—users with basic programming skills and domain knowledge—

are lacking, and these users should be supported with more tools to construct advanced visualizations. We

outline our approach to how savvy users can be engaged more in the development process and construct

advanced visualizations. Information visualization community should focus more on moving the boundary of

constructing advanced visualizations from expert users towards savvy users.

1 INTRODUCTION

Several Information Visualization (InfoVis) toolkits

and tools ((Fekete, 2004), (Bederson et al., 2004),

(Heer et al., 2005), (Bostock et al., 2011), (Spot-

ﬁre, 2011), (Tableau, 2011), (Omniscope, 2011)) have

been developed, especially in the last decade. The

purpose is to enhance the visualization development

process, provide better presentation of data, and lead

users towards novel simple and advanced visualiza-

tions. However, constructing meaningful visualiza-

tions is not an easy task for users, considering their

programming skills. Heer et al. (2008) categorize

users in three groups: Novice Users are the ones

with no programming skills but they have the domain

knowledge and basically interact with predeﬁned vi-

sualizations; Expert Users are users with very good

programming skills who construct advanced visual-

izations and have no domain knowledge; and Savvy

Users, who have some basic programming skills and

an understanding of the domain. Savvy users act as

an intermediate between novice and expert users, try-

ing to bridge the gap between domain expertise and

programming knowledge.

The vast variety of data types, user tasks and

needs, etc., premises that “one visualization does not

ﬁt all”. Therefore, researchers seek new approaches

to construct novel advanced visualizations. Advanced

visualizations is a broad deﬁnition, but in this paper,

we refer to advanced visualizations as those that use

position, size, shape and color for data and are pro-

grammatically constructed (e.g. LifeLines (Plaisant

et al., 1998), SparkClouds (Lee et al., 2010), Life-

Flow (Wongsuphasawat et al., 2011)).

In this paper, we investigate 13 InfoVis toolkits

and tools, and compare to what extent they can be

used by the user. Our ﬁndings show that savvy users

are neglected by academia and industry, although they

are often the most valuable users. To make use of

their domain and programming knowledge, new ap-

proaches and tools should be developed. Novice

users, the main target of commercial tools, are lim-

ited to the predeﬁned visualization templates, and ex-

pert users are assisted mainly by academia with ﬂexi-

ble and customizable libraries. Finally, we outline our

approach to how savvy users can be engaged more in

the development process and construct advanced vi-

sualizations.

2 RELATED WORK

Heer et al. (2008) discuss how new audiences can

participate in creation and collaboration of visualiza-

tions. Based on user skills, the authors categorize

them in three groups: novice, savvy and expert users.

For each user type, authors focus on two main aspects

of InfoVis tools: exploration-analysis and communi-

731

Pantazos K. and Lauesen S..

CONSTRUCTING VISUALIZATIONS WITH INFOVIS TOOLS - An Evaluation from a User Perspective.

DOI: 10.5220/0003860507310736

In Proceedings of the International Conference on Computer Graphics Theory and Applications (IVAPP-2012), pages 731-736

ISBN: 978-989-8565-02-0

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

cation. Although, the authors present some tools as-

sociated with each group, they mainly focus on the

collaborative visualization aspect rather than on the

construction process of the visualizations.

A recent study (Grammel et al., 2010) investigates

how novice users construct visualizations and reﬂects

on how to overcome the barrier of visualization exper-

tise. Their ﬁnding shows that there is a need for tools

that facilitate novice users in selecting appropriate vi-

sualizations and engaging them in an iterative process

to reﬁne visualizations. Although this study provides

insights for novice users, it does not evaluate toolkits

and tools from the novice-user perspective. Our work

focuses on all types of users and to what extent they

can use the existing toolkits and tools.

Wohlfart et al. (2008) evaluated four InfoVis tools

investigating their capabilities in visualizing tempo-

ral data. Their ﬁndings showed that existing tools

are limited in visualizing temporal data and future re-

search should focus in this ﬁeld. However, this study

does not compare the tools from a user perspective,

neither how visualizations are constructed.

3 COMPARISON SETTING

3.1 InfoVis Toolkits and Tools

In our study, we selected 13 toolkits and tools de-

veloped in the last decade from academia and indus-

try. We searched on the web for commercial Info-

Vis tools, and selected six most well-known tools in

the ﬁeld: Spotﬁre (Spotﬁre, 2011), Tableau (Tableau,

2011), Omniscope (Omniscope, 2011), MS Excel

(Excel, 2011), Google Chart Tools (Google-Chart-

Tools, 2011) and Many Eyes (Viegas et al., 2007).

Secondly, we used ACM Portal and IEEE website to

ﬁnd InfoVis tools and toolkits. Initially, we ranked

the results based on the total number of citations,

and then we selected only the appropriate ones by

reading the abstracts. Finally, we read all the pa-

pers and we selected the ﬁve most appropriate toolk-

its: Prefuse (Heer et al., 2005), The InfoVis Toolkit

(Fekete, 2004), Piccolo (Bederson et al., 2004), Proto-

vis (Bostock and Heer, 2009) and Improvise (Weaver,

2004). During the process of reviewing the existing

literature, we identiﬁed two more visualization toolk-

its —Processing (Processing, 2011) and Flare (Flare,

2011). Due to the fact that Proccesing uses its own

programming language and has a development envi-

roment, and Flare is written in ActionScript, we de-

cided to use these tools in our evaluation as well.

Due to time constraints, we chose only these toolk-

its and tools, which we believe are a good represen-

tative sample from academia and industry. Some of

the tools identiﬁed in our study, which are not in-

cluded in this evaluation, but readers may be inter-

ested are: D3 (Bostock et al., 2011), Obvious (Fekete

et al., 2011), Dave (Vrachnos and Jimoyiannis, 2008),

ComVis (Matkovic et al., 2008), Mondrian (Lienhard

et al., 2007) and Jazz (Bederson et al., 2000).

3.2 Comparison Dimensions

In this study, we investigated how information visu-

alizations are constructed by the user. Below, we

present 5 dimensions that we used to evaluate each

toolkit and tool: (1) Who constructs the visualization;

(2) What type of visualizations can the user construct;

(3) Does it support construction of advanced visual-

izations; (4) How are visualizations speciﬁed and cre-

ated; (5) Does it have a development environment?

We investigated these dimensions for each type of

user: novice, savvy and expert.

4 EVALUATION

4.1 Prefuse

Prefuse (Heer et al., 2005) was created at University

of Berkley and is developed in Java. Visualizations

in Prefuse are constructed using a set of ﬁner-grained

building blocks and specifying operators that deﬁne

the layout and behavior of these blocks. This toolkit

is used by expert users, who are skilled java pro-

grammers. Expert users can develop simple and ad-

vanced visualizations programmatically. This toolkit

can be integrated in an Integrated Development Envi-

ronments (IDE), such as Eclipse, but this integration

does not support features such as drag and drop, what-

you-see-is-what-you-get (WYSIWYG) panel, and so

forth. The purpose of this tool is to facilitate ex-

pert users work. However, the user has to have a

good knowledge of the toolkit; otherwise complexity

may arise even for programmers (Bostock and Heer,

2009). In conclusion, savvy and novice users cannot

use this toolkit to construct visualizations.

4.2 The InfoVis Toolkit

The InfoVis Toolkit (Fekete, 2004), developed at Uni-

versity of Paris-Sud, is another Java based visualiza-

tion toolkit that uses several interactive components

to construct visualizations, for instance range sliders.

Providing a consistent framework, the InfoVis toolkit

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732

Figure 1: Improvise development environment.

assists expert users in constructing simple and ad-

vanced visualizations, which are speciﬁed program-

matically. Moreover, it allows expert users to ex-

tend the toolkit with new components and integrate

visualization techniques into interactive applications.

However, creating and customizing visualizations re-

quires experienced programmers. Consequently, this

toolkit is not appropriate for savvy and novice users.

Finally, the InfoVis toolkit, similar to Prefuse(Heer

et al., 2005), does not have a specialized development

environment, but it can be integrated in IDE such as

Eclipse.

4.3 Piccolo

Piccolo (Bederson et al., 2004) was developed at Uni-

versity of Maryland and has a version in Java and C#.

This toolkit is mainly used for developing graphical

applications with rich user interfaces. Piccolo sup-

ports the development of information visualizations

indirectly, as it does not support visualization tech-

niques (Heer et al., 2005). Nevertheless, novel visu-

alizations such as LifeFlow (Wongsuphasawat et al.,

2011) are based on this toolkit. Users can use vi-

sualization functionalities and components, such as

zooming, animation and range slider. This toolkit can

be used only by expert users, and the fact that it does

not support visualization techniques directly, it makes

it more challenging even for expert users. Similar to

the previous two toolkits, this toolkit does not have a

specialized development environment either.

4.4 Flare

This visualization toolkit is the successor of Prefuse

(Heer et al., 2005), but is written in ActionScript.

Flare (2011) supports expert users with a number of

simple and advanced visualizations. To construct a

visualization, expert users need to specify in Action-

Script the properties of the visual objects (e.g., posi-

tion, shape, color), and sequential commands to cre-

Figure 2: An arc diagram using Protovis.

ate the visualization. Skillful programmers can also

deﬁne new operators and visual objects. However,

advanced programming knowledge is required. Flare

can be integrated in Adobe Flex IDE and it does not

come with a specialized IDE. This toolkit cannot sup-

port novice or savvy users in constructing advanced

visualizations.

4.5 Improvise

Improvise (Weaver, 2004) is a visualization toolkit

for creating multi-view coordination visualizations

for relational data. It was developed at University of

Wisconsin Madison, and is written in Java. Expert

and savvy users can create visualizations by specify-

ing expressions for simple shared-object coordination

mechanism. Shared-objects in Improvise are graphi-

cal attributes such as color, font, etc. Improvise has

a specialized development environment where users

can create views by adding frames, controls, deﬁning

variables and attaching data using the lexicon work

area (a central repository where information related to

the data and database are saved) . Users can construct

simple and advanced visualizations based on the pre-

deﬁned controls. Finally, this tool can be used by

savvy users. Figure 1 shows a screenshot of Impro-

vise.

4.6 Processing

Processing was developed initially “to teach funda-

mentals of computer programming within a visual

context” to newcomers, but it has grown into a more

complete tool for constructing images, animations

and interactions (Processing, 2011). Processing has

a development environment, where expert users can

type the speciﬁcation for a visualization and preview

the results. The development environment is similar

to a regular IDE. To create a visualization, users have

to know another programming language, Processing.

CONSTRUCTING VISUALIZATIONS WITH INFOVIS TOOLS - An Evaluation from a User Perspective

733

As a result, this tool is used only by expert users, or

non-programmers who pursue a programmer carrier.

4.7 Protovis

Protovis (Bostock and Heer, 2009), developed at

Stanford University, supports expert users to con-

struct visualizations using its domain speciﬁc lan-

guage. Designers can combine primitive graphical

controls, called marks, bind them to data, and spec-

ify visual properties. Protovis is implemented in

JavaScript, and events can be attached to a mark using

anonymous functions. In Protovis, expert users can

create simple and advanced visualizations. The au-

thors of Protovis have compared the speciﬁcations for

a simple pie chart in Protovis, Processing and Flare,

showing that the visualization in Protovis is speciﬁed

in fewer lines of code. Protovis does not have a spe-

cialized development environment to support visual-

ization creation. Constructing visualizations in Pro-

tovis may be a potential solution for savvy users due

to the simplicity of the speciﬁcations. Figure 2 shows

an arc diagram and a part of the speciﬁcations for this

visualization.

4.8 MS Excel

MS Excel is a spreadsheet program that allows users

to analyze and visualize data (Excel, 2011). With sim-

ple steps, users can construct visualizations based on

predeﬁned templates (e.g. bar chart, pie chart, etc.).

MS Excel users can specify spreadsheet formulas or

use standard widgets to construct visualizations in the

worksheet area. However, advanced visualizations

cannot be constructed by novice users, or by savvy

users. Expert users can construct advanced visualiza-

tions by means of Macros, which can be integrated in

MS Excel.

4.9 Tableau

Tableau (2011) is a commercial visualization tool, the

successor of Polaris (Stolte and Hanrahan, 2000) de-

veloped at Stanford University. Tableau allows all

types of users to create visualizations by dragging and

dropping ﬁelds onto axis shelves (vertical and hori-

zontal areas) and using visual speciﬁcations. Tableau

uses VizQL (Hanrahan, 2006), an algebraic speciﬁ-

cation language, to create views based on predeﬁned

templates and bind data to them. Further, it has a

powerful interactive development environment where

users can interact, ﬁlter, sort data and create interac-

tive dashboards. The main users of this tool are novice

users. However, they may encounter some challenges

Figure 3: Evaluation results.

during the learning phase, such as mapping data to

visual objects. Tableau is a “black box” system. As

a result, expert users do not have access to the ker-

nel of the system and it is not possible to extend the

system. Therefore, users can not construct advanced

visualizations that are not supported by the tool.

4.10 Spotﬁre

Spotﬁre (2011) is another commercial tool for data vi-

sualizations. It supports users with a number of visu-

alization techniques, who can interact with the devel-

opment environment and create visualizations based

on predeﬁned ones. Once they have selected the data

and chosen the type of visualization, the tool gen-

erates automatically the visualization. Furthermore,

users can create dashboards, by combining different

visualizations (bar chart, scatter plot, etc) in a single

screen. As in Tableau, users can not create advanced

visualizations except from the predeﬁned ones.

4.11 Omniscope

Omniscope (2011) is in the same category as Tableau

and Spotﬁre, and shares similar features such as inter-

active dashboard, etc. Although it can be used by all

types of users, the main scope of this tool is to support

novice users in constructing visualizations, as Spot-

ﬁre and Tableau do. Visualizations are constructed

based on predeﬁned templates. Novel advanced visu-

alizations cannot be constructed with this tool. Expert

users can not extend the system with new controls or

functionalities, as it is a “black box” system.

4.12 Google Chart Tools

Google Chart Tools (2011) is a library written in

JavaScript that provides several predeﬁned simple

(e.g. line chart, scatter chart, etc.) and advanced

chart types (e.g. Image multi color bar chart, Mo-

tion Chart Time Formats, etc.). Visualizations can be

IVAPP 2012 - International Conference on Information Visualization Theory and Applications

734

Figure 4: Evaluation results.

constructed by expert users in the web-based develop-

ment environment named Code Playground, Figure 3.

The Code Playground environment increases the like-

lihood of attracting savvy users, who may ﬁnd this

approach easier to understand and use. In addition,

Google Chart Tools has the Live Chart Playground to

test charts already created in the Code Playground. In

this one, the user can change some parameters and

see how the visualization changes. Expert and savvy

users are limited to predeﬁned templates and func-

tions, and cannot construct novel advanced visualiza-

tions.

4.13 Many Eyes

Many Eyes (Viegas et al., 2007), developed at IBM

Research Center, is a web-based visualization plat-

form mainly for novice users. In Many Eyes, visual-

izations are implemented in Java Applets. Users con-

struct a visualization in three steps: upload a dataset;

choose a visualization from predeﬁned ones; cus-

tomize and publish the visualization. Many Eyes au-

tomatically generates and shows the visualization on

the screen. Visualizations other than predeﬁned ones

are not supported.

5 RESULTS

Figure 4 summarizes the results of our evaluation.

Our ﬁndings show that academia focuses mainly on

supporting expert users to construct novel advanced

visualizations. On the other hand, industry markets

their products towards novice users, assisting them

with predeﬁned visualization templates. Although

both communities can beneﬁt from engaging savvy

users in constructing better advanced visualizations,

savvy users are neglected and not supported as novice

and expert users are. Our study shows that only one

toolkit, Improvise (Weaver, 2004), may support savvy

users in constructing advanced visualizations. A po-

tential toolkit for savvy users may be Protovis (Bo-

stock and Heer, 2009), due to the simplicity of its

domain speciﬁc language. Finally, the results show

that novice users are supplied with interactive envi-

ronments where they can drag and drop, get real-time

feedback, ﬁlter, sort and so forth.

Although there is a need for more creativity in the

InfoVis ﬁeld, existing savvy users can not utilize their

knowledge and construct novel visualizations. As a

result, the InfoVis community should investigate how

savvy users can construct advanced visualizations.

We are developing a solution that deals with the

dimensions in this way: (1) Who Constructs the Vi-

sualization? We aim savvy users who will be able to

utilize both the domain knwoledge and their program-

ming skills to produce novel visualizations. (2) How

are Visualizations Speciﬁed and Created? Users

can use building-blocks and specify spreadsheet-like

formulas that link building-blocks. Spreadsheet for-

mulas have proved to be a successful approach among

programmers as well as non-programmers (Burnett

et al., 2001). They experiment with them in the de-

velopment environment and deploy them to novice

users. (3) What Type of Visualizations can the User

Construct? Simple and advanced visualizations can

be constructed using relational data, or data trans-

formed into a relational format. (4) Does it Support

Construction of Advanced Visualizations? Spec-

ifying spreadsheet-like formulas, which allow prop-

erties such as color, position etc. to be data depen-

dent, and using building blocks, we believe that savvy

users will be able to combine them in innovative and

advanced visualizations. For instance, SparkClouds

(Lee et al., 2010) can be composed by combining a

SparkLine block with a WordCloud block. (5) Does

it have a Development Environment? We are devel-

oping a specialized development environment where

savvy users can drag and drop building blocks, spec-

ify formulas with intellisense, see results live, etc.

The development environment facilitates users work,

and our evaluation clearly shows that all tools for

novice users have one.

To summarize, our goal is to move the boundary in

constructing advanced visualization from a program-

ming style towards a more expressive style for non-

programmers, by means of spreadsheet-like formu-

las. In addition, we believe that a specialized devel-

opment environment will facilitate savvy users’ work

even more.

6 CONCLUSIONS

In this paper, we evaluated 13 popular InfoVis toolk-

its and tools from a user perspective. This study

CONSTRUCTING VISUALIZATIONS WITH INFOVIS TOOLS - An Evaluation from a User Perspective

735

concludes that present tools do not support savvy

users—users with basic programming skills and do-

main knowledge—in constructing advanced visual-

izations, although their role is crucial. They need dif-

ferent visualization tools to construct advanced visu-

alizations. This study can serve as a brief introduction

to newcomers in the InfoVis area. For a deeper un-

derstanding, we encourage them to refer to the refer-

ences mentioned in this paper. Moving the boundary

of constructing advanced visualizations from expert

users towards savvy users is a research area that re-

quires more the attention of the InfoVis community.

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