TOWARDS A WEB PORTAL DATA QUALITY MODEL

Angélica Caro

Universidad del Bio Bio, Departamento de Auditoria e Informática, La Castilla s/n, Chillán, Chile

Coral Calero, Ismael Caballero, Mario Piattini

Universidad Castilla-La Mancha, Departamento de Informática, Paseo de la Universidad 4, Ciudad Real, España

Keywords: Data Quality, Information Quality, Web Portals.

Abstract: The technological advance and the internet have favoured the appearance of a great diversity of web

applications, one of them are Web Portals. Through this, organizations develop their businesses in a more

and more competitive environment. A decisive factor for this competitiveness is the assurance of data

quality. In the last years, several research works on Web Data Quality have been developed. However, there

is a lack of specific proposals for web portals data quality. In this paper, we will present a proposal for a

model data quality for web portals based on some web data quality works.

1 INTRODUCTION

In the last years, a growing interest in the subject of

Data Quality (DQ) or Information Quality (IQ) has

been generated because of the increase of

interconnectivity of data producers and data

consumers mainly due to the development of the

internet and web technologies. The DQ/IQ is often

defined as “fitness for use”, i.e., the ability of a data

collection to meet user requirements (Strong, Lee et

al. 1997; Cappiello, Francalanci et al. 2004). Data

Quality is a multi-dimensional concept (Cappiello,

Francalanci et al. 2004), and in the DQ/IQ literature

several frameworks providing categories and

dimensions as a way of facing DQ/IQ problems can

be found. One of the most used and referred to is the

framework proposed by (Strong, Lee et al. 1997)

that states a classification based on the users

perspective. Furthermore, methodologies that allow

us to manage DQ/IQ within an organization have

been proposed. Among them, we can mention:

TDQM (Strong, Lee et al. 1997), AIMQ (Lee 2002)

and TQdM (English 2001).

Research on DQ/IQ started in the context of

information systems (Strong, Lee et al. 1997; Lee

2002) and it has been extended to contexts such as

cooperative systems (Fugini, Mecella et al. 2002;

Marchetti, Mecella et al. 2003; Winkler 2004), data

warehouses (Bouzeghoub and Kedad 2001) and

electronic commerce (Aboelmeged 2000;

Katerattanakul and Siau 2001), among others. Due

to the characteristics of web applications and their

differences from the traditional information systems,

the community of researchers has recently started to

deal with the subject of DQ/IQ on the web with

great interest (Gertz, Ozsu et al. 2004).

Related to web, some years ago appeared web

portals. However, there are no works on DQ/IQ

specifically developed for web portals. As the

literature shows that DQ/IQ is very dependent on the

context, we centre our work in the definition of a

Data Quality Model for web portals. For doing it we

use some works developed for other web but that

can be applied to our particular context. For

example, we use the work of (Yang 2005) where a

quality framework for web portals is proposed

including the data quality as part of it.

The aim of this paper is to show the result of a

review about works in DQ/IQ on the web context

and how we have used it for the development of the

first version of a web portal DQ model. This paper is

organized as follows: in section 2 we show some

DQ/IQ issues associated with the web context,

DQ/IQ frameworks and methods for evaluation and

improvement of DQ/IQ on the web and some web

quality characteristics identified from de studied

works. In section 3 we present our proposal based on

189

Caro A., Calero C., Caballero I. and Piattini M. (2006).

TOWARDS A WEB PORTAL DATA QUALITY MODEL.

In Proceedings of the Eighth International Conference on Enterprise Information Systems - SAIC, pages 189-192

DOI: 10.5220/0002491501890192

 SciTePress

the previously showed review. Finally, section 4

concludes with our remarks and future work.

2 DATA QUALITY ON THE WEB

In this section we review the most important aspects

about web DQ/IQ that we founded on the literature.

2.1 Issues About Web Data Quality

Due to the own nature of the web, some concrete

issues directly related to the DQ/IQ arise. For

example (Eppler and Muenzenmayer 2002), states

that typical problems of a web page affect the

DQ/IQ as design problems that make it difficult

users access to information. Other issue is the

integration of structured and non-structured data

(Finkelstein and Aiken 1999) and integration of data

from different sources (Naumann and Rolker 2000;

Angeles and MacKinnon 2004; Bouzeghoub and

Peralta 2004; Gertz, Ozsu et al. 2004; Winkler

2004). In both cases the challenger is achieve

integrated data that probably do not have the same

level of DQ/IQ, and are delivered to the user with a

fit level for use. Also, in this context is very

important approach the DQ/IQ from users

perspective (Angeles and MacKinnon 2004;

Cappiello, Francalanci et al. 2004; Gertz, Ozsu et al.

2004) and to help them to understand data and their

quality (Finkelstein and Aiken 1999; Gertz, Ozsu et

al. 2004).

Finally, the demand for real-time services (Amirijoo,

Hansson et al. 2003) and the dynamism on the web,

particularly the dynamism with which data,

applications and sources change (Pernici and

Scannapieco 2002; Gertz, Ozsu et al. 2004), can

affect quality.

The identification of these problems, and maybe

others that we have not identified still, reveal us the

necessity to create specific proposals to this context

to approach the DQ/IQ, since otherwise they cannot

be considered all their particularities.

2.2 Web Data Quality Frameworks

By using a DQ/IQ framework, organizations are able

to define a model for data environment, to identify

relevant quality attributes, to analyze attributes

within both current and future contexts and to

provide a guide to improve DQ/IQ. In the literature,

we have found some proposals oriented to DQ/IQ on

the web. Among them, we can highlight the ones

proposed in (Katerattanakul and Siau 1999; Fugini,

Mecella et al. 2002; Pernici and Scannapieco 2002;

Eppler, Algesheimer et al. 2003; Graefe 2003;

Bouzeghoub and Peralta 2004; Gertz, Ozsu et al.

2004; Melkas 2004; Moustakis, Litos et al. 2004).

This summary of the frameworks that we have

studied, gives us a global idea of the diversity of

focuses that can be considered in the analysis of the

DQ/IQ in the web. Through them we can identify

the outstanding characteristics of quality to the data

in this context.

Once is defined a framework it is possible to

approach the quality of the data from the evaluation

perspectives and it improves. From the above-

mentioned frameworks we can find many methods

of DQ evaluation and improvement. These methods

can be used by the organizations to help the users

and IT managers to capture and analyze the state of

DQ in a web application.

2.3 Web Data Quality Characteristic

From de studied works, we have identified 100 data

quality characteristic. The most considerate are:

Accuracy, in 60% of the works; Completeness, in

50% of the works and Timeliness, in 40% of the

works. Concise, Consistent, Currency, Interpreta-

bility, Relevance, Secure, in 30% of the studies.

As a conclusion of all these antecedents we think

that it is necessary a general quality framework for

data on the web that include all the possible

characteristics related to them. But not only the

quality characteristics are necessary for defining the

general DQ/IQ framework, also the problems and

different perspectives about the data of the web

would be also taken in to account. In particular, the

data consumer’s expectative.

3 THE DQ/IQ WEB PORTAL

FRAMEWORK

There is currently no established conceptual

foundation for developing and measuring DQ/IQ of

Web applications in general, and Web Portal in

particular. Our aim is to create a DQ/IQ framework

for Web Portals, considering the next basic

considerations:

1. We started with de DQ attributes proposed in the

literature. These are the ones identified from the

study mentioned previously.

2. We use the data consumer’s perspective. We

consider the work about quality of data on Internet

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of (Redman 2000). He proposes the next categories

for the data consumer’s expectative: Privacy,

Content, Quality of values, Presentation,

Improvement and Commitment.

3. We considered the 11 basic functionalities for a

Web portal proposed by (Collins 2001): Data Points

and Integration, Taxonomy, Search Capabilities,

Help Features, Content Management, Process and

Action, Collaboration and Communication,

Personalization, Presentation, Administration, and

Security.

With these elements we first relate the web portal

functionalities with data consumer’s perspective

about data quality. As a result we obtain a matrix

(see figure 1). We use the each cell for filling in it

those Web DQ/IQ attributes applicable

(functionality, expectation).

As a matter of example the functionality “Data Point

and Integration” connects to: “Privacy” (users

expect privacy about the sources and their

integration), “Content” (the consumers need a

description of portal areas covered, uses of the

published data, etc.), “Quality values” (data points

correct, current and complete), “Presentation”

(formats, language, and others are very important for

a easy interpretation) and “Improvement” (user

wants to participate with their opinions in the portal

improvements knowing the result of applying them).

Then we determined for each relation DQ/IQ

attributes cab be applied. Table 1 shows the

classification done for the “Data Point and

Integration”. Due to space restrictions in this

example we consider only three DQ/IQ attributes.

Expectation Dimensions

Privacy Confidentiality, Maintainable,

Verifiability

Content Accuracy, Concise, Consistent

Quality of

Values

Accuracy, Consistent,

Interpretability

Presentation Consistent, Amount of data, Clear

Improvement Accessibility, Traceability, Clear

However, it will be necessary to validate this

assignation. For doping it, we plan to work with

user’s portals through surveys and questionnaires.

Once the validation will be finished, we will

reorganize the attributes obtaining the final version

of the DQ/IQ web portal matrix.

4 CONCLUSIONS AND FUTURE

WORK

The great majority of works found in the literature

show that DQ/IQ is very dependent on the context.

The increase of the interest in the development of

web applications has implied either the appearance

of new proposals of frameworks, methodologies and

evaluation methods of DQ/IQ or the adaptation of

the already-existing ones from other contexts such as

Traditional Information Systems, Cooperative

Information Systems and Data Warehouses. In this

paper, we have described different issues associated

with DQ/IQ on the web; many of them are still of

great interest for the community of researchers.

There are different proposals related to DQ/IQ on

the web either to establish quality criteria and/or

dimensions relevant to this context or to establish

strategies to evaluate and measure these criteria.

We have used the study done for the web DQ/IQ as

basis for developing a DQ/IQ model for web portals.

In this paper we have showed the first version of this

model. The model is composed by two dimensions:

the consumer expectations and the web portals

functionality. As an example we have classified

some web quality characteristics for one of the

functionalities and for all the user expectations. As

future work, in one hand we must fill in all the cells

of the defined matrix with quality characteristics

and, on the other hand, to validate the classification

in order to prove its correctness.

Table 1: DQ for Data Point and Inte

ration.

Figure 1: Consumer expectations vs. web portals

functionalit

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191

ACKNOLEDGEMENTS

This research is part of the following projects:

CALIPO (TIC2003-07804-C05-03) supported by

Ministerio de Ciencia y Tecnología (Spain) and

DIMENSIONS (PBC-05-012-1) supported by

FEDER and by the “Consejería de Educación y

Ciencia, Junta de Comunidades de Castilla-La

Mancha” (Spain).

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