Survey Report on Data Presentation and Visualization for NCCP

by

Likhitha Ravi

Advisor: Dr. Sergiu Dascalu

July 19, 2012

Department of Computer Science and Engineering

College of Engineering

University of Nevada, Reno

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Table of Contents

1. Introduction…………………………………………………………… 2

2. Existing Methods……………………………………………………… 2

3. Visualization Tools……………………………………………………. 3

4. Matrix……………………………………………………………….....18

5. Discussion……………………………………………………...………28

6. Future Work ……………………………………………………………29

7. References………………….…………………………………………..30

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1. Introduction

The purpose of this document is to provide the summary of survey results on visualization tools used for

data presentation and visualization of environmental data. Section 2 discusses the existing visualization

methods for environmental data. Section 3 lists the existing visualization tools of different domains and

states their usability in research for large datasets. Section 4 provides a matrix with the features of

visualization tools. Section 5 presents a general discussion about the state of art in data visualization. In

Section 6 the future research directions in field of data visualization are discussed. Section 7 has the list

of references.

2. Existing Methods

The existing visualization methods for environmental data can be classified based on several factors.

Many researchers have introduced taxonomy for visualization techniques [1]. Shneiderman [2] classified

visualization techniques based on data types and user tasks. The data types include 1D, 2D, 3D,

multidimensional, temporal, tree, and network. Some of the user tasks on which Schneiderman

classified the methods were overview, zoom, filter, details-on-demand, relate, history, and extract.

Keim [3] classified them based on data types and interaction/distortion techniques. His data types were

similar to those of Schneiderman expect for algorithms/software. The interaction methods such as

standard, projection, filtering, zoom, distortion, link brush was considered for classification. Silva et al.

[23] classified them based on visualization and interaction features, Muller et al. [24] classifies them as

static and dynamic, Chi [25] classified them based on visualization process and Tory [26] classified them

based on the characteristics of models of data. These classifications more generic, in this paper we have

introduced the taxonomy for visualization methods based on the data types of environmental data.

The data types of the environmental data are one-dimensional such as atmospheric pressure, wind

velocity; two-dimensional variables is a result of combination of two variables for example temperature

and humidity; three-dimensional variables are a combination of three variables; multidimensional is a

combination of more than three variables; and finally climate related text can be found in the

documents or news.

2.1 One-Dimensional

For a one dimensional data set, the data values correspond to one variable and there is only value per

data item. Some of the data visualizations of one-dimensional data are histogram as in figure 4.2 in [4],

and normal distribution as in figure 4.10 in [4].

2.2 Two-Dimensional

Two-Dimensional data corresponds to two variables. The relationship between two variables can be

easily found through visualization. The 2D visualizations of climate data are line graph as in figure 3. (d)

in [5], comparison of variables using plotting as in figure 3 in [6], bar chart as in 7.13 in [7], area chart,

pie chart, maps, scatterplot as in 7.3 as in [8] , stream line and arrow visualization as in figure 1 in [9].

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2.3 Three-Dimensional

Data values in three-dimensional space have three attributes. The graphical representation of the three

attributes shows the depth and rotation in addition to the two dimensional data. The methods for

representing three-dimensional data are Isosurface techniques figure 9 in [10] and fig [2] in [11], direct

volume rendering figure 2.5 in [12], slicing techniques as in figure 3 in [13], 3D bar charts and realistic

rendering figure 5 in [14].

2.4 Multi-Dimensional

Data attributes in Multi-Dimensional space ranges from four to hundreds. To understand the relations

between multiple variables several techniques are available. The methods for the visualization of

multivariate data are scatterplot matrix as in figure 1 in [15], parallel coordinates figure 2 in [16], star

coordinates as in figure 1 in [17], maps as in figure 9 in [18], and autoglyph as in 9 in [19].

2.5 Text

The structured and unstructured text in climate change related documents can be visualized using

phrase net as in [20], wordle as in [27], and word tree\word net as in [21].

3. Visualization Tools

In this section, several visualization tools, their applicability, references, strengths, limitations and

authors’ comments have been stated. These tools are designed to meet the needs of different user

groups. The goal of the survey was to find several visualizations options for the environmental data by

considering tools that performs diverse tasks such as statistical analysis, numerical analysis, 1D graphs,

2D graphs, 3D graphs, multivariate visualizations and textual visualizations.

Tool Name ArcGIS

Overview It is Geographical Information System (GIS). It is used in data analysis by using

simple maps.

Applicability Geology, hydrology, meteorology, environmental sciences.

References ArcGIS online

http://www.arcgis.com/about/

ArcGIS – Wikipedia, the free encyclopedia

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

Strengths It reduces cost by efficiently using the hardware and software.

It supports several data types.

It is available in many versions such as desktop, mobile, and web map

version.

Easy to use interface.

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Limitations ArcGIS occasionally hangs during the installation of registrations.

Comments It is used by many researchers around the world because of its high quality

graphics, scalability and flexibility.

Tool Name AVS/Express

Overview It supports object oriented development and is mainly used for visualization

purposes by programmers and non-programmers.

Applicability Engineering, Fluid Dynamics, earth sciences, business, medicine, manufacturing

telecommunications and environmental research.

References AVS/Express-Visualization Edition-Data Visualization

http://www.avs.com/products/avs-express/visualization.html

Strengths Easily integrates modules from programming languages such as C, C++,

and FORTRAN.

Handles complex and large datasets.

Limitations It depends on virtual memory for sending results to user which gives low

performance at times.

No zooming facility.

Comments It provides powerful visualizations for researchers but zooming in and get more

details of the data is difficult.

Tool Name DataScape

Overview It is a data modeling and visualization tool for complex systems.

Applicability Soft Sensors, Business Intelligence, Process Modeling, Embedded Applications

References Datascape - Overview

http://www.tmpinc.com/datascape_overview.html

Strengths Good graphics.

Identifies the unusual data.

Limitations Not intuitive.

Comments It does not have a very big user group. It is mostly convenient for professionals.

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Tool Name Ferret

Overview It is an interactive data analysis and visualization tool for large grid data sets.

Applicability Oceanography, climatology.

References Data Visualization and Analysis - Ferret http://ferret.wrc.noaa.gov/Ferret/

Strengths Supports input data from several data sources.

Good quality graphics.

Good memory management for large datasets.

Limitations UNIX, Linux machines need X windows software to run Ferret.

Comments It can be used by researchers working mainly in oceanography and climatology.

Tool Name GGobi

Overview It is used for the visualizations of high dimensional data.

Applicability Engineering, fluid mechanic, meteorology, electromagnetism, and dynamical

systems.

References GGobi data visualization system

http://www.ggobi.org/

GGobi - Wikipedia, the free encyclopedia

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

Strengths Good data visualization capabilities.

Extensibility through plugins.

It is open source.

Limitations Not very intuitive.

Comments A good choice for professionals in the visualization field.

Tool Name Google Visualization API

Overview One stop for visualizations over the web. The API provides visualizations for

structured data which can be integrated into a website or gadget.

Applicability Engineering, social sciences, and environmental.

References Google Visualization API Reference - Google Chart Tools - Google Developers

https://developers.google.com/chart/interactive/docs/reference

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Strengths Connects to several data sources.

Easy to embed visualization to an existing website.

Several visualization options.

Saves lots of programming time.

Easy to set up.

Limitations Limited to web- based applications.

Limited styling options.

Comments Good choice for beginners who have less knowledge in programming.

Tool Name GrADS

Overview Grid Analysis and Display System (GrADS) a visualization tool is used for data

manipulation, visualization in 5-dimensional space.

Applicability Earth sciences.

References GrADS Home Page

http://www.iges.org/grads/grads.html

Strengths Open source.

Supports several input data formats.

Limitations Not very intuitive.

Comments Need programming background. But a good tool for researchers of earth

sciences.

Tool Name Graphpad

Overview It is used to analyze, organize and plot data.

Applicability Biostatistics, scientific graphing, Education, Medicine, and pharmaceutical.

References GraphPad Software. Scientific graphing, curve fitting (nonlinear regression)

statistics.

http://www.graphpad.com/welcome.htm

Strengths It is able to import/ export data from excel.

Many products with different graphing packages are available.

Limitations It is expensive for the features it provides.

Comments It is not recommended for huge databases and exploratory tasks.

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Tool Name Integrated Data Viewer (IDV)

Overview It is a java based software framework used to analyze and visualize the

geoscience data.

Applicability Environmental sciences, climatology.

References Unidata

http://www.unidata.ucar.edu/software/idv/

Strengths It is free.

Provides high quality 3D visualizations.

It can plot data from remote servers.

Supports several data types.

Limitations It requires a lot of RAM which makes it slow for large databases.

Comments It is a good tool for researchers working on supercomputers with lot of RAM and

need high quality graphics.

Tool Name Jquery visualize

Overview It is a plugin which uses JavaScript to generate simple charts in HTML5.

Applicability Web applications, multidomain.

References Update to jQuery Visualize: Accessible Charts with HTML5 from Designing with

Progressive Enhancement | Filament Group, Inc., Boston, MA

http://www.filamentgroup.com/lab/update_to_jquery_visualize_accessible_char

ts_with_html5_from_designing_with/

Strengths Flash is not required.

Draws chart from HTML table.

Default styling can be altered using CSS.

Limitations Limited visualizations.

Need HTML5 which is not supported by older versions of IE. It need IE6 +.

No animations.

Comments Not a very good choice for creating rich and sophisticated visualizations but

perfect for creating easy and simple visualizations.

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Tool Name Many eyes

Overview It is a web based tool. Users can upload datasets, analyze those using

visualizations, and share them with others.

Applicability Climatology, social sciences, networking, politics, multidomain.

References Many Eyes

http://www-958.ibm.com/software/data/cognos/manyeyes/

Strengths Big active user community.

No software is required.

No installation required

Free visualizations of the user datasets that can be shared.

Limitations Application is not available for mobile devices and tablets like

iphone/ipad as java and flash is required.

Comments The site is still under development. Many visualizations relating to climate

change are available. It allows viewers to add comments on visualizations, so it

good place to post the work and get reviewers from other users. Also, users get

to know the most popular and highly rated visualizations.

Tool Name Map objects

Overview It is a set of software components that embeds maps into applications.

Applicability address/intersection search, census point-in-polygon processing, parks GIS,

traffic counts GIS

References Using MapObjects for Enterprise GIS at The City of Calgary

http://proceedings.esri.com/library/userconf/proc01/professional/papers/pap8

42/p842.htm#mapobjectsapplications

Strengths Very simple and easy to use.

Limitations It supports only windows operating system.

Limited features.

Comments It is a good choice for programmers working with Visual Basic and trying to

develop mapping applications.

Tool Name Mathematica

Overview It is a software package which does several numerical computations and

symbolic computations for data analysis and visualization.

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Applicability Mathematics, engineering, fluid mechanic, meteorology, electromagnetism, and

dynamical systems.

References Wolfram Mathematica: Technical Computing Software- to

Solution

http://www.wolfram.com/mathematica/

Strengths Good quality graphics.

Good naming conventions.

Limitations Interpreter is very slow.

Extensions are expensive.

Comments This tool is very useful in research areas which need lot of computation and less

programming.

Tool Name Matlab

Overview It is developed by MathWorks. It is a programming language that allows users to

perform data analysis, visualization, algorithm development and numerical

computation. It supports 1D, 2D, and 3D visualizations.

Applicability Signal and image processing, data analysis and exploration, visualization,

programming and application development, communications, control design,

test and measurement, financial modeling and analysis, and computational

biology.

References MATLAB –The language of Technical Computing.

http://www.mathworks.com/products/matlab/

MATLAB – Wikipedia, the free encyclopedia

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

Strengths It cuts development time as no programming is needed for computing

complex calculations, and visualizing the results.

Generates very powerful graphics.

Many ready to use functions

Excellent online help.

Ease of use.

Operating system independent.

Limitations It is an interpreted language, so it could be slow.

Expensive.

Comments Although it allows us to perform visualizations, it is not devoted to visualization.

It is mostly used for complex numerical computations. Working with n-

dimensional data could be very challenging.

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Tool Name Minitab

Overview It is used for statistical analysis and graphing.

Applicability Statistical analysis, quality improvement, plotting graphs, social sciences and

educational.

References Software for Statistics, Process Improvement, Six Sigma, Quality - Minitab http://www.minitab.com/en-US/default.aspx

Minitab - Wikipedia, the free encyclopedia

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

Strengths Easy to use and learn.

Analysis can be performed using macros.

Requires less disk space.

Limitations Reading input data from other packages is not easy.

Not a good choice to perform complex numerical analysis.

Comments It is mainly used by beginners who would like to learn statistics. It cannot be used

for intensive research. The analysis requires manual programming using macro

which could be time consuming.

Tool Name NCAR Command Language (NCL)

Overview It is an interpreted language used for scientific data analysis and visualization.

Applicability Scientific Visualizations.

References CISL's NCAR Command Language (NCL)

http://www.ncl.ucar.edu/

Strengths Open source

Several data input and output formats.

Limitations Not very intuitive.

Comments It needs knowledge in programming. Not a very good tool for beginners.

Scientists need to learn a new language to explore the data.

Tool Name OpenDX

Overview It is open source software developed by IBM. It supports the data analysis and

visualization of complex applications.

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Applicability Petroleum Modeling, Demographic Modeling, Environmental Modeling,

Molecular Graphics, Medical Imaging, Weather Modeling.

References Open Visualization Data Explorer

http://www.opendx.org/

Strengths It is a very powerful data visualization tool.

Built in macros are provided to facilitate the functionalities required by

the users.

Suitable for programmers with different skill sets, as it supports

languages like C, FORTRAN and Visual Basic.

It has a client –server architecture.

It is free.

Limitations It is not suitable for all of MAC machines.

It requires more memory.

Comments Researchers can analyze the complex datasets by creating their own macros. The

techniques provided by the tool helps the researchers gain new insights of the

data.

Tool Name Prefuse

Overview It is a toolkit for data interaction, modeling and visualization. It is a java based

library.

Applicability Biology, social sciences, geography.

References prefuse | interactive information visualization toolkit

http://prefuse.org/

Strengths More flexibility as the java modules can be changed as needed.

Data manipulation can be done easily.

Limitations Visualizations do not work on mobile devices.

Integration with other components is not easy.

Comments It is not suitable for time varying continuous data analysis.

Tool Name Processing.js

Overview It is a java based open source programming language used for programming

images, animations, and interaction.

Applicability Arts, animations, simulations, 3D graphics and designing.

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References Processing.js

http://processingjs.org/

Strengths No need of Flash for interactions.

Limitations It doesn’t support all browsers.

It doesn’t support object level events

Comments It needs knowledge some scripting programming language. It is mostly used by

artists and designers.

Tool Name Qlikview

Overview It is a data analysis and visualization tool used mainly in the field of business

intelligence for decision making.

Applicability Business intelligence.

References Business Discovery: Business Intelligence For Everyone | QlikView

http://www.qlikview.com/

Strengths Good dashboard support.

Good data interactivity.

Links to data from excel.

Limitations The feedback for developers while manipulating controls is not quick.

Comments It works best for someone connecting to several data sources and doesn’t

modify the data analysis often.

Tool Name R

Overview It is GNU software. It is a semi object oriented tool. It is used for statistical

computing and graphics.

Applicability Environmental sciences, Finance, Genetics, Machine Learning, Social Sciences,

Spatial.

References Introduction to Splus and R

http://faculty.nps.edu/sebuttre/home/S/intro.html

Strengths Excellent Graphics.

S-PLUS and R are similar tools but R is free.

It is extensible.

Documentation is freely available.

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Limitations Computation is slow compared to other tools like Matlab.

It does not have a GUI.

Comments This tool should be a perfect choice for professionals in data analysis field and

someone who loves programming.

Tool Name S-PLUS

Overview It has a GUI which can be used for data analysis and building graphs. It is written

in C++ and is based on S programming language. S is an object oriented and

interpreted language.

Applicability Biology, bioinformatics, medicine, genetics, environmental statistics and life

sciences.

References Introduction to S-PLUS (and R)

https://home.comcast.net/~lthompson221/SPLUS_Manual.pdf

Strengths Excellent Graphics.

Menus and dialogs are available to create graphs.

Easy C and FORTRAN interface.

Documentation is freely available.

Limitations It is very expensive compared to R which has similar features and free.

Some programming skills are needed.

Comments It can be used if cost doesn’t matter and when GUI is essential.

Tool Name SPSS

Overview It has a GUI which is written in java. It is used for data analysis and generating

graphics using simple menu options. It is an acronym of Statistical Package of

Social Sciences. PSPP is a free replacement of SPSS.

Applicability Social sciences, marketing, medicine, surveys, government, education, and

marketing.

References SPSS - Wikipedia, the free encyclopedia

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

IBM SPSS software

http://www-01.ibm.com/software/analytics/spss/

Strengths Very intuitive. Basic computing knowledge is enough to start with.

Data entry can be done using simple spreadsheet.

Data variables can be added easily based on the existing ones.

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It is suitable for large datasets.

It can find unusual data easily before analysis.

Limitations It is not useful for complex surveys and research.

Few regression analysis techniques are missing.

Does not involve cluster analysis.

It is Windows based.

Comments It is mostly used in social sciences. Although it can generate interesting graphs

such as histogram, scatterplots, boxplots, it can create complex 3D graphics and

maps.

Tool Name SQL Server Reporting Services

Overview SSRS helps in decision making by generating tabular, interactive and graphical

reports of multidimensional data.

Applicability Business Intelligence.

References SQL Server Reporting Services - Wikipedia, the free encyclopedia

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

Reporting Services (SSRS) http://msdn.microsoft.com/en-us/library/ms159106.aspx

Strengths Allows connections with several data sources like SQL, Oracle, and SSAS.

Can be integrated with visual studio.

Limitations The predefined set of visualizations does not allow the users to explore

new ways in visualization.

Comments It is a good tool to learn the basics of data analysis and visualization using

Microsoft technologies.

Tool Name Tableau

Overview It is tool for interactive data visualization and analysis.

Applicability Banking, government, medicine, education, and telecommunications.

References Fast Analytics and Rapid-fire Business Intelligence from Tableau Software |

Tableau Software

http://www.tableausoftware.com/

Tableau Software - Wikipedia, the free encyclopedia

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

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Strengths It takes less time to implement.

Very good data interactivity.

Excellent data integration with other tools.

Limitations Very poor data modeling.

Comments It is good for beginners to learn different kinds of visualization, not a good

choice for experienced developers.

Tool Name UV-CDAT

Overview Ultrascale Visualization Climate Data Analysis Tools. It provides data analysis and

visualization for large climate datasets.

Applicability Climatology.

References UV-CDAT http://uv-cdat.llnl.gov/

Strengths A good of climate related data visualizations.

Supports provenance functionality.

Open source.

Limitations Supports very limited operating systems.

As it is a new product, it is prone to bugs.

Comments Very good tool for researchers working with climate related data. Different data

visualizations can be explored.

Tool Name VisTrails

Overview It is an open source system that provides support for scientific data workflow and

visualization.

Applicability NASA, environmental sciences, astrophysics, biomedicine, neuro imaging, and

climate modeling.

References VisTrailsWiki

http://www.vistrails.org/index.php/Main_Page#VisTrails_Overview

VisTrails: visualization meets data management

http://dl.acm.org/citation.cfm?id=1142574

Strengths Simple and easy user interface.

Broad user community.

Good comparative visualization.

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Limitations Sometimes it may hang up while updating large amounts of data from a

remote site.

Limited parallel computing capabilities.

Comments A good tool for researchers who wants to explore different workflows and

compare the results of variables of large datasets.

Tool Name VisIt

Overview It is an open source tool which provides data visualization for complex scientific

data.

Applicability Astrophysics, environmental sciences, fluid dynamics, and molecular science.

References VisIt - Wikipedia, the free encyclopedia

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

VisIt: An End-User Tool For Visualizing and Analyzing Very Large Data http://vis.lbl.gov/Publications/2011/Childs-SciDAC2011.pdf

Strengths It provides framework for customization.

It provides interactive parallel visualization.

Reads data of different formats.

Limitations Data movement could be challenging in future machines.

Comments Visit can handle datasets ranging from billions to trillions, so it is good tool for

researchers working on super computers.

Tool Name Visualization toolkit (VTK)

Overview It is open source software. It is supports object oriented environment and

consist of libraries written in C++. It is mainly used for data processing and

visualization.

Applicability Scientific computing, Acoustic field visualization, virtual reality, medicine,

computational geometry, rendering and Image processing.

References VTK - The Visualization Toolkit

http://www.vtk.org/

Strengths Manages and represent complex scientific data.

Support many visualization techniques.

Big user community.

Limitations VTK has limited modeling techniques.

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Data interaction is limited.

User interface is not very intuitive.

Comments It is a good tool for researchers working with complex and large datasets but it is

not a choice for the nonprogrammers.

Tool Name Weave

Overview It is Web-based Analysis and Visualization Environment. Users can visualize large

datasets of any kind.

Applicability Business, social sciences, environmental sciences, mulitdomain.

References Weave (Web-based Analysis and Visualization Environment)

http://oicweave.org/

Strengths Many kinds of visualizations are available.

It is open source and free.

Limitations It is still under development. Understanding the needs of different user

groups, and providing tutorials is a challenging task.

Comments Researchers can look into the demos and screenshots to understand the latest

visualization techniques.

Tool Name XmdvTool

Overview It is a software package for multivariate visual exploration.

Applicability Remote sensing, financial, geochemical, census, and simulation data.

References Xmdv Home page: Overview

http://davis.wpi.edu/xmdv/index.html

Strengths Very powerful, high quality visualizations.

Limitations Handling large datasets requires lot of memory.

There is a limit on user number of dimensions.

Comments A good tool for exploring the multivariate visualization techniques.

4. Matrix

A matrix is designed to represent the features of the visualization tools discussed in Section 3. The tool name, organization or people responsible for the

development of the tool, supporting operating systems, approximate price, supporting visualization techniques, tool type, required or supporting

programming languages, type of user Interface, and number of variables and dimensional supported by the tool are discussed in Table 1.

Table 1: Matrix representing the features of visualization tools [28].

# Tool

Name

Developer Operating

system

support

Open

source

/Propriet

ary

Price Visualization

Techniques

Application

Type

Programmi

ng/

Scripting

languages

Interf

ace

# of variables

1 ArcGIS Esri Microsoft

Windows,

Linux,

Sun

Solaris

Proprieta

ry

$2,500 -

$17,500

Map (MXD), Globe,

Geoprocessing,

Geocoding, Network

Analysis,Geodata ,

Mobile

Visualization

tool

VBA , VB,

.NET, Java,

C++, COM,

Python,

VBScript,

JavaScript,

ASP, JSP,

ColdFusio

n, Java,

.NET,

JavaScript,

XML,

FLASH,

PHP

GUI Multidimens

ional data

2 AVS/Expr

ess

AVS Windows,

Mac OS X,

Linux,

Proprieta

ry

Starts at

$2,995

2D line field plots,

Gamma plot, 3D

shaded,contour, and

Toolkit C, C++,

and

FORTRAN.

GUI/

CGI

2D, 3D,

univariate,m

ultivariate

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Solaris,

and HP-

UX, IRIX

and Alph

Tru64

arrow field plots,

Animations, particle

tracing using stream

lines and streak

lines, isosurfaces,

Volume

Visualization

data

3 DataScap

e

Third

Millennium

Production

s

Windows,

Linux

Open

source

Free Visualization data

points, Surface

visualizations

Visualization

tool

C++ GUI 2D, 3D,

multivariate

data

4 Ferret Thermal

Modeling

and

Analysis

Project

(TMAP) at

National

Oceanic

and

Atmospheri

c

Administra

tion

(NOAA)/

Pacific

Marine

Environme

ntal

Unix

systems,

and on

Windows

XP/NT/9

x

Open

Source

Free Geophysical

formatting,

symmetrical

processing.

scripting

language

Ferret

Scripts

CLI 3D, 4D,

Multidimens

ional data

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Laboratory

(PMEL)

5 GGobi Deborah .S,

Michael .L,

Hadley. W,

Duncan .T

.L, Di Cook,

Heike .H

and

Andreas .B

Windows,

Mac, Unix

Open

source

Free Histogram, textured

dot plot, barchart,

spineplot,

Scatterplot, parallel

coordinates, time

series plot

Visualization

tool

Ggobi

scripting

GUI/

CGI

3D,

Multivariate

data

6 Google

Visualizat

ion API

Google Windows,

Mac, Unix

Open

source

Free pie chart ,

Scatterplot, Guage,

geo chart, bar chart,

tree map, bubble

chart, line graph,

stack graph, , combo

chart, column chart,

area chart,

candlestick chart,

word cloud

generator, and

maps.

Toolkit Javascript GUI 2D

7 GrADS COLA Linux,

Mac OS X,

Windows,

Solaris,

Open

source/

GNU

General

Free line and bar graphs,

scatter plots,

smoothed contours,

shaded contours,

scripting

language

FORTRAN,

GrADS

scripts

CLI 5-

dimensional

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IBM AIX,

DEC

Alpha,

IRIX

Public Lic

ense

streamlines, wind

vectors, grid boxes,

shaded grid boxes,

and station model

plots

8 Graphpad GraphPad

Software,

Inc.

Mac,

Windows

Proprieta

ry

$595 Line graphs, column

graphs, symbol

graphs, bar graphs,

Linear and

nonlinear regression

Analysis

Graphics,

Curve fitting,

and

Statistics

tool

No

programm

ing or

scripting

required

GUI 2D

9 Integrate

d Data

Viewer

(IDV)

Unidata Windows,

Linux,

Solaris

(SPARC

and x86),

Mac OS-X

Open

source

Free Charts, maps, radar

displays, gridded

data displays,

isosurfaces, volume

rendering, globe

display, plan view,

profiler winds

Software

library

Java GUI 3D, multi-

dimensional

data

10 Jquery

visualize

jQuery

Team

Windows,

Mac, Unix

Open

source

Free pie charts, line

charts, bar charts

and area charts

JavaScript

library

Javascript No

GUI

2D

11 Many

eyes

IBM Windows,

Mac OS X,

Linux and

Unix

Open

source

Free Scatterplot, matrix

chart, network

diagram, bar chart,

block histogram,

bubble chart, line

graph, stack graph,

Visualization

tool

No

programm

ing or

scripting

required

GUI 2D

Survey Report

- 22 -

pie chart, tree map,

word tree, tag cloud,

phrase net, word

cloud generator, and

maps.

12 Mapobjec

ts

ESRI Windows Proprieta

ry

Free Maps Visualization

tool

Visual

Basic, C++

and

Delphi

GUI 2D

13 Mathemat

ica

Wolfram

Research

Windows,

Mac,

Unix

Proprieta

ry

$2,495

(Professio

nal),

$1095

(Educatio

n), $140

(Student),

$69.95

(Student

annual

license)

$295

(Personal

)

polar and spherical

plots, contour and

density plots,

parametric line and

surface plots, and

vector, stream plots,

candlestick charts,

quantile plots, box

whisker charts,

Bode plots,

histograms, 2D and

3D bar charts, pie

charts, bubble

charts, B-spline

curves in 2D or 3D

Software

Package

C++, Java,

.Net,

FORTRAN,

CUDA,

OpenCL

GUI/

CGI

2D, 3D

14 Matlab The

MathWorks

Linux,

Microsoft

Windows

Proprieta

ry

Starts at

$99.99 for

students

Line, area, bar, pie

charts, Histograms,

Scatter/bubble

plots, Animations,

Statistical

tool

C, C++,

and

Fortran.

GUI/

CLI

1D,2D, 3D

visualization

s

Survey Report

- 23 -

Direction and

velocity plots,

isosurfaces, Volume

Visualization

15 Minitab Minitab Inc. Windows Proprieta

ry

$895–

$1395[2]

perpetual,

$542 or

less

concurren

t annual,

$29.99/$

49.99/$9

9.99

academic

Tables, Graphs,

Regression Analysis,

factor analysis,

cluster analysis,

correspondence

analysis, Time series

plots

Statistics

tool

C,

FORTRAN

GUI/

CLI

Multivariate

data

16 NCL

National

Center for

Atmospheri

c

Research (

NCAR)

Linux,

MacOSX,

AIX, and

Cygwin/X

running

on

Windows.

Open

source

Free Histograms, Line

graphs, bar charts,

box plots,

scatterplots, area

charts, markers,

wind barbs, maps,

isosurfaces, and

other graphical

objects.

scripting

language

NCL

scripts, C,

FORTRAN

CLI 1D,2D, 3D

17 OpenDX IBM Windows,

Mac OS X,

Linux,

Open

source

Free Animations,

Direction and

velocity plots,

Visualization

tool

C,

FORTRAN

and Visual

GUI 2D, 3D,

univariate,m

ultivariate

Survey Report

- 24 -

Solaris,

and Unix

isosurfaces, Volume

Visualization

Basic data

18 Prefuse Research

team at

University

of

Maryland

Windows,

Mac, Unix

Open

source

Free Area chart, Bar

chart, Pie chart,

scatter chart, line

graph, Tree map,

network diagram

and animations

Toolkit Java CGI 2D

19 Processin

g.js

Ben Fry

and Casey

Reas,

Linux,

Mac OSX,

Windows

Open

source

Free Animations, Graphs,

Charts, digital art,

video games

Toolkit Processing

,

JavaScript,

No

GUI

2D, 3D

20 qlikview QlikTech

team

Windows Proprieta

ry

$1350/

per user,

$15,000 /

concurren

t license,

Scatterplot, matrix

chart, bar chart,

area chart, bubble

chart, stack graph,

pie chart, link map

and spatial maps

Visualization

tool

Java GUI 2D,

univariate,

multivariate

data

21 R R

Foundation

Windows,

Mac OS X,

Linux and

Unix

Open

source

Free Graphs, traditional

statistical tests, time

series analysis,

linear & nonlinear

modeling,

classification,

clustering

Statistics

tool

C, Python,

Perl

GUI/

CLI

3D

Survey Report

- 25 -

22 S-PLUS Insightful

Inc.

Windows,

Linux,

UNIX,

Solaris

Proprieta

ry

$2399/ye

ar

Graphs, linear &

nonlinear modeling,

classification,

clustering

Statistics

tool

FORTRAN,

C, S

GUI 3D

23 SPSS IBM Windows,

Mac, and

Linux

Proprieta

ry

$4975 Tables, graphs,

linear regression,

cluster analysis, and

non-parametric

tests

Statistics

tool

Java,

Python,

SaxBasic

GUI/

CLI

2D

24 SQL

Server

Reporting

Services

Microsoft Windows Proprieta

ry

$1095-

Academic

$2434-

Commerci

al use

Area charts, bar

charts, column

charts, maps, line

charts, polar charts,

range charts, shape

charts, sparklines,

data bars

scatterplots, stock

charts

Visualization

tool

SQL GUI 2D,3D

univariate,

multivariate

data

25 Tableau Research

team lead

by

Professor

Pat

Hanrahan

at Stanford

Uiniversity

Windows Proprieta

ry

$999

(Desktop)

, $1999

(Professio

nal), Free

version

(Tableau

Public)

Scatterplot, matrix

chart, bar chart,

area chart, bubble

chart, stack graph,

pie chart, link map

and spatial maps

Toolkit No

programm

ing or

scripting

required

GUI 2D,

univariate,

multivariate

data

26 UV-CDAT Team Mac, Open Free multi-view Toolkit Python, No 3D, multi-

Survey Report

- 26 -

supported

by Office of

biological

and

environme

ntaresearc

h (BER)

Linux source visualization,

Direction and

velocity plots,

isosurfaces, Volume

Visualization, and

parameter space

exploration

C/C++,Jav

a,

FORTRAN

GUI dimensional

data

27 VisTrails Team at

University

of Utah

Windows,

Mac,

Linux

Open

source

Free multi-view

visualization,

Direction and

velocity plots,

isosurfaces, Volume

Visualization, and

parameter space

exploration

Toolkit Python GUI 3D, multi-

dimensional

data

28 VisIt Lawrence

Livermore

National

Laboratory

Windows,

Mac,

Linux,

Unix, AIZ,

Solaris,

Tru64,

IRIZ

Open

source

Free Contour 3D, Pseudo

color plot, Contour

3D, volume plot,

vector plot, subset

plot, molecule plot,

parallel axis plot

Toolkit Python CLI 3D, multi-

dimensional

data

29 Visualizat

ion toolkit

(VTK)

Kitware

Research

group

Windows,

Mac,

Unix

Open

source

Free scalar, vector,

tensor, texture,

volumetric methods,

implicit modeling,

polygon reduction,

mesh smoothing,

Toolkit C++ No

GUI

3D

Survey Report

- 27 -

cutting, contouring,

and Delaunay

triangulation

30 Weave Research

team at

Institute

for

visualizatio

n and

perception

research of

UMASS

Lowell

Windows,

Mac OS X,

Linux and

Unix

Open

source

Free Scatterplot, matrix

chart, network

diagram, bar chart,

block histogram,

bubble chart, line

graph, stack graph,

pie chart, tree map,

word tree, tag cloud,

phrase net, word

cloud generator, and

maps.

Visualization

system

Flex, Java GUI 2D

31 XmdvTool Team supp

orted by

NSF

UNIX,

LINUX,

MAC and

Windows

Open

source/

GNU

General

Public Lic

ense

Free parallel coordinates,

scatterplots,

dimensional

stacking and star

glyphs

Visualization

tool

Eclipse

using Qt

GUI 2D,

univariate,

multivariate

data

5. Discussion

In this section we will discuss about the state of the art in data visualization. An effective data

visualization system should be able to assist users with the data analysis of large data sets by using the

latest available techniques. From the matrix in Table 1 we it is clear that most of the tools which are

being used for research purposes provides the visualization techniques such as charts, graphs,

volumetric modeling, flow visualization, spatial visualization, temporal visualization, parallel coordinates

plot, Contour 3D, 3D maps, 3D/2D scatterplots, isosurfaces, and star glyphs.

Apart from the visualizations techniques that provided by the tools discussed in the table 1, there are

few techniques which are not available in these tools. Volume splitting is one of the techniques in which

a volume is divided into several semantic components [29]. Volume rendering algorithm is then applied

on each component. This will save enormous time and complexity mainly in the field of medicine. This

technique is not yet available in many existing tools. Slice based volume rendering is also used in cloud

modeling [30]. Another 3D modeling technique used to represent complex organic shapes and structural

relationship in biology and chemistry is Metaballs [31]. It is mostly used in DNA structure, organic forms

visualization, and molecular images. A meatball is a defined by 3D field variable which varies its value

with its distance from the center and influences its surrounding particles. Graph, tree visualizations are

used in defining the taxonomies of large-scale species [32]. 3D volumetric interactive information

visualization is used for representing information in several documents visually so that it helps in

understanding them easily without reading the entire document [33]. It presents stereoscopic viewing

with glyph based rendering.

Most of the data especially in the field of meteorology, environmental sciences and climatology is kept

open in the World Wide Web (WWW) for the researchers, policy makers and general public [34,35,36] .

This data can be of several formats such as simple csv, xls, and xml. The source code of many

visualization tools is also available in their website which encourages the researchers in the field of

visualization to implement their ideas quickly by not having to start everything from scratch.

IBM is providing a web-based visualization tool called Many Eyes [37] which lets users to visualize the

datasets without installing any software on their machines. Users need to upload their dataset and

choose a visualization technique. It does not provide high quality 3D graphics which is often need in

research areas. In future, there might be similar web sites in each field which helps researchers and

public in visualizing their datasets over internet with high quality graphics needed in their domain. Also,

these could be available on mobile devices and tablets in coming days.

Now-a-days, with the existence of high quality computer display devices, visualization is mainly focused

on 3D/4D techniques. The benefits of these techniques replacing the 1D/2D techniques which have

been in use since many years need to be investigated. User interaction with the visualizations is also

increasing. Users are able to discover many details available in the visualization by rolling the mouse

over the visualization, and are able to change the visualization by using functions like zoom in, zoom out,

moving left, right or by selecting several views for example Google maps provides all of these features in

its visualizations [38].

Survey Report

29

6. Future Work

The demand for data analysis and visualization is increasing day by day in fields like business,

engineering, education, physical science, biology, social science, meteorology, finance, genetics, and

hydrology. After surveying thirty one data visualization tools of different domains it is clear that there

are many issues facing the researchers/designers in the field of data visualization. Each tool is mainly

addressing the needs of a particular application domain which makes it not very useful in other

application domains. But, it is very important for the designers of the visualization tool to get familiar

with several visualization techniques that have been developed for other domains, this will help them in

understanding the difference between a good user interface from a bad one and also gives new options

for visualization in his/her domain which others might not have thought about. To identify the possibility

of new technique, the designer should have insights of the data and user needs thoroughly and then

find new techniques. If there is a possibility of new technique he/she should be able to find the

advantages of it over the existing visualization techniques and see if the existing computation method is

more informative than the new visualization technique. Also, the new technique/tool should look similar

to the existing tools of the domain, and use the most widely used latest technologies to appeal the

users. Although it mainly addresses the needs of a particular domain, it is a grand success if it is

applicable in several other domains.

Other challenges facing the designers of the data visualization include creating applications that can run

on several devices such as desktop, mobile phones, display walls, and touch pads; support diverse

operating systems such as Windows, Mac, and UNIX; provide several visualization options so that users

does not need another tool; provide various interaction techniques; provide high quality graphics with

no loss of useful information; support most of the existing input data formats; support large datasets

with no performance issues; and easy integration with other tools. Apart from including these features

designers should also consider the characteristics of data. Data can be static, dynamic, structured,

unstructured, spatial, nonspatial, scalar, and vector. Understanding the different characteristics of data

and providing a linkage between these types is a very challenging task. As the developed visualizations

play a very crucial role in decision making it is important to check if there are any missing data values

from defective equipment, and if the received data is accurate. The cognitive and perceptual levels of

the users should be considered while designing the tool. Interaction techniques should be given a new

look with the changes and improvements in hardware, skillset of potential users, and decision making

needs.

To conclude, the future work in the field of data visualization can be focused on either finding new ways

of visualization or searching for problems in the existing visualization techniques or solving the existing

problems in the data visualization field. Although, it is hard to guess but it is also not impossible to find

an area with large volumes of ever increasing time varying data that needs to be analyzed and

visualization techniques have not been in that field applied so far and build the a new tool for that

application domain. The designer should have apt knowledge in that domain and data visualization to

build an effective and useful tool.

Survey Report

30

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