INTERACTIVE ANALYSIS OF MULTIDIMENSIONAL DATA ON

THE WEB BY USING TIME-TUNNEL

Seiji Okajima and Yoshihiro Okada

Graduate School of Information Science and Electrical Engineering, Kyushu University

744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan

Keywords: Data and knowledge visualization, Interactive data analysis, Web application.

Abstract: In recent years, the Internet has become popular in various application fields so that a huge number of data

records are generated and stored on the web. In this situation, we need any tool that helps us to analyze such

multidimensional data for obtaining new findings from those data. In this paper, we introduce a visual and

interactive analysis tool for multidimensional data called Time-tunnel. Time-tunnel visualizes any number

of time series numerical data records as individual charts each of which is displayed on an individual

rectangular plane called data-wing in a 3D virtual space. Through direct manipulations on a computer

screen, the user easily puts more than two data-wings overlapped together to compare their charts in order to

recognize the similarity or the difference among those data records. Simultaneously a radar chart among

those data at any time point is displayed to recognize the similarity and the correlation among them. This

time, the authors extended Time-tunnel to make it available on the web and this paper clarifies the

usefulness of web-version Time-tunnel by showing practical analysis examples.

1 INTRODUCTION

This paper treats a visual and interactive analysis

tool for multidimensional data called Time-tunnel

developed by our research group (Akaishi and

Okada, 2004; Akaishi and Okada, 2005). This time,

we extended Time-tunnel to make it available on the

web and this paper clarifies the usefulness of web-

version Time-tunnel by showing practical analysis

examples.

Time-tunnel visualizes any number of time-

series numerical data records as individual charts in

a virtual 3D space. Each chart is displayed on a

rectangular plane called data-wing. The user easily

puts more than two different data-wings overlapped

together to compare their data represented as charts

in order to recognize the similarity or the difference

among them. Simultaneously a radar chart among

those data at any time point is displayed in the same

3D space to recognize the similarity and the

correlation among them. However, in Time-tunnel,

only one chart is displayed on one data-wing. If

there are a huge number of time-series numerical

data records, the user has to prepare accordingly

such a huge number of data-wings and practically it

becomes impossible to interactively manipulate

them. To deal with this problem, we enhanced the

functionality of Time-tunnel to enable it to display

the Parallel Coordinates on each data-wing (Notsu et

al., 2005). Due to this functionality enhancement,

the user can visually analyze a huge number of time-

series numerical data records through interactive

manipulations on a computer screen. Furthermore, it

becomes available for the visual analysis of multi-

dimensional data, i.e., database records with a huge

number of attributes by preparing multiple data-

wings, dividing multi-attribute data into several sets

by attributes, and displaying each set of data as

Parallel Coordinates on each data-wing.

In recent years, the Internet has become popular

in various application fields so that a huge number

of data records are generated and stored on the web.

In this situation, we need any tool that helps us to

analyze such a huge number of data records

effectively, e.g., visually and interactively, on the

web. This time, we extended Time-tunnel to make it

available on the web.

The remainder of this paper is organized as

follows. First of all, Section 2 describes related work

and points out the difference of our tool from theirs.

Section 3 introduces details of Time-tunnel and its

Parallel Coordinates version. Then, Section 4

415

Okajima S. and Okada Y.

INTERACTIVE ANALYSIS OF MULTIDIMENSIONAL DATA ON THE WEB BY USING TIME-TUNNEL.

DOI: 10.5220/0001838204150418

In Proceedings of the Fifth International Conference on Web Information Systems and Technologies (WEBIST 2009), page

ISBN: 978-989-8111-81-4

describes implementation of Time-tunnel as a web

application. Section 5 presents data analysis

examples using web-version Time-tunnel. Finally

we conclude the paper in Section 6.

2 RELATED WORK

For the visualization of multidimensional data,

Inselberg and Dimsdale introduced Parallel

Coordinates (Inselberg and Dimsdale, 1990), which

visualizes multiple data records as multiple poly-

lines on the same 2D plane at the same time. After

their proposal of Parallel Coordinates, many

modified versions having a variety of additional

features were proposed. For instance there is method

(Artero, 2004, Graham, 2003; Fua, 1999; Johansson,

2005; Siirtola, 2000; Hauser, 2002) that draws poly-

lines in adequate colors and transparency levels

according to their crowding densities, and there is a

similar method for the same purpose (Graham, 2003)

that draws curbed lines instead of poly-lines to

indicate high crowding dense attribute values.

Although we have not implemented these techniques

yet, it is possible technically to introduce them into

our Parallel Coordinates version of Time-tunnel. We

are supposed to do that. Also, there is a unique

proposal (Johansson, 2005) that visualizes Parallel

Coordinates by vertical axes each stands on a circle

in a 3D space. One more vertical axis stands at the

center of the circle. This axis corresponds to the

user selected attribute of database records and other

vertical axes standing on the circle correspond to

several attributes most strongly related to the center

axis attribute. This proposal is interesting but is not

directly related to our proposed system. Our

proposed Parallel Coordinates version of Time-

tunnel visualizes multiple charts like Parallel

Coordinates on one individual rectangular plane.

Time-tunnel originally provides multiple data-wings

in a virtual 3D space so that if the user has a huge

amount of data records, he/she can analyze them by

separating into several groups using multiple

rectangular planes. This is the one advantage of our

Parallel Coordinates version of Time-tunnel.

Another popular data analysis method is based

on star chart or radar chart. As the similar tools,

there are Star Glyphs of XmdvTool (Ward et al.,

1994) and Stardinates Tool (Lanzenberger and Miksch,

2003). Stardinates Tool has combined feature of

Parallel Coordinates and Glyphs (Ward et al., 1994).

Our Time-tunnel has combined feature of Parallel

Coordinates and star chart (radar chart) visualization

tool with interactive interfaces. Moreover, Time-

tunnel has also aspects as a multimedia presentation

tool. These points are further differences of our

Parallel Coordinates version of Time-tunnel from

the above visual analysis tools.

3 TIME-TUNNEL

In this section, we introduce original Time-tunnel

and Parallel Coordinates version of Time-tunnel.

First of all, we describe system configuration of

original Time-tunnel, its components and how Time-

tunnel works for the analysis of multidimensional

data, especially multiple time-series numerical data.

After that, we show Parallel Coordinate version of

Time-tunnel.

3.1 System Configuration

Time-tunnel consists of three main types of

components, i.e., data-wing, time-plane and time-bar.

Parent-child relationships among data-wings, time-

planes and time-bar are as shown in Figure 1.

Rotation-bar works as the hinge and the parent of

data-wing, and time-bar is the parent of each

Rotation-bar.

Figure 1: Component structure of Time-tunnel.

3.1.1 Data-wing

Data-wing has a shape like a sheet. It displays one

multidimensional data, one time-series numerical

data, as a chart on its sheet. For the visualization of

multiple data, the user can use multiple data-wings

as he/she wants. Each data-wing is connected to

time-bar by its hinge. The hinge is also another

component that has a rotation functionality called

rotation-bar. Therefore, by rotation operations on

data-wings, the user can put multiple charts

overlapped together to compare them. Each time-

series numerical data of each data-wing is sent to

WEBIST 2009 - 5th International Conference on Web Information Systems and Technologies

416

time-bar through rotation-bar. Data-wing keeps one

time-series numerical data. It makes a chart from the

data and displays the chart on its surface.

3.1.2 Time-plane

Time-plane also has a shape like a sheet. Time-

plane is connected to time-bar perpendicular to data-

wings and used for displaying a radar chart. Figure 2

shows its detail of the radar chart. Its position data is

sent to time-bar to specify a time of data among

charts to be displayed as a radar chart. Actually

time-plane is connected to time-bar through

translation-bar. Time-plane moves along time-bar by

the user manipulations on the translation-bar,

because the translation-bar is the parent of time-

plane.

Figure 2: Radar chart display.

3.1.3 Time-bar

Time-bar has a thin, long cylindrical shape. Time-

bar works as a time pivot of data-wings. It collects

multiple time-series numerical data from each data-

wing and displays a radar chart on one of time-

planes.

3.2 Parallel Coordinates Version of

Time-tunnel

When visualizing a large number of time-series

numerical data records, the user has to prepare

exactly the same number of data-wings. To deal with

this problem, we extended the functionality of data-

wing as explained in the following.

Figure 3 shows Parallel Coordinates version of

Time-tunnel. We extended data-wing to enable it to

display more than two time-series numerical data

records, i.e., multiple database records as multiple

charts, in it like Parallel Coordinates. Even if there

are a huge number of database records to be

visualized, the user can divide them into several

groups and assign each group to one of the multiple

data-wings of the same Time-tunnel. Since Time-

tunnel has multiple data-wings and displays multiple

Parallel Coordinates using those data-wings, it is

easy to separate database records shown on one

data-wing and to visualize each of them on each of

the multiple data-wings.

Figure 3: Parallel Coordinates version of Time-tunnel.

In this way, the user can visualize a huge number

of database records using Parallel Coordinates

version of Time-tunnel. The user can select one

record that he/she wants to analyze in each data-

wing and the selected chart is soon highlighted.

Since the user can rotate and put any data-wings

overlapped together, he/she can compare his/her

selected records by looking at highlighted charts.

Furthermore, a radar chart among the selected charts

can also be displayed similarly to original Time-

tunnel.

4 IMPLEMENTATION OF

TIME-TUNNEL AS A

WEB APPLICATION

The original Time-tunnel is developed using

IntelligentBox (Okada and Tanaka, 1995) which is a

constructive visual software development system for

interactive 3D graphic applications. IntelligentBox

applications run only on the IntelligentBox system

so that the user needs to install IntelligentBox in

order to use original Time-tunnel.

Web version of Time-tunnel is realized as a flash

content by ActionScript programming with the use

of Papervision3D ActionScript library. The user can

use Time-tunnel through a web browser in which

Adobe Flash Player plug-in is installed. So, it is

possible to provide Time-tunnel functionalities as

one of the SaaS (Software as a Service) applications.

In addition, Web version of Time-tunnel has

JavaScript API to allow the user to embed Time-

tunnel functionalities in his/her own web page and

MashUp is also possible. The functions provided by

the Time-tunnel API are specifically to create new

Time-tunnel in a 3D virtual space, to add new data-

INTERACTIVE ANALYSIS OF MULTIDIMENSIONAL DATA ON THE WEB BY USING TIME-TUNNEL

417

wing to current Time-tunnel, to read database

records and to assign them to data-wings, and so on.

5 DATA ANALYSIS EXAMPLE

This section introduces data analysis example.

Figure 4 shows a web service example consisting of

two Time-tunnels. This web service analyzes

company information. One of the Time-tunnels

shown in the left part of Figure 4 has multiple data-

wings each of which displays multiple Parallel

Coordinates. Each data-wing of the Time-tunnel

displays database records of each of the three kinds

of Japanese companies, i.e., finance companies,

industry companies, and food stuff companies.

These database records have fourteen types of

attributes, e.g., head-count, number of recruitment,

beginning salary, and so on.

Another Time-tunnel shown in the right part of

the figures displays time-series stock data

categorized into three on three data-wings put

overlapped together. In this way, the user can

analyzes database records interactively on the web.

Figure 4: Web service example to analyze company

information by using two Time-tunnels together.

6 CONCLUSIONS

In this paper, we introduced interactive visualization

tool called Time-tunnel and proposed web version of

Time-tunnel to analyze multidimensional data on the

web. Then, we described its usefulness by showing a

practical data analysis example using real database

records.

As future works, we will propose a new analysis

tool that is realized as a combination of Time-tunnel

and another web API. We also have to evaluate the

usefulness of Time-tunnel by consulting actual users

who use it.

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