TOWARDS A DATA QUALITY MODEL FOR WEB PORTALS

Research in Progress

Angélica Caro

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

Coral Calero, Ismael Caballero, Mario Piattini

ALARCOS Research Group

Information Systems and Technologies Department, UCLM-Soluziona Research and Development Institute

University of Castilla-La Mancha, Paseo de la Universidad, 4 – 13071 Ciudad Real, Spain

Keywords: Data Quality, Information Quality, Web Portals.

Abstract: The technological advances and the use of the internet have favoured the appearance of a great diversity of

web applications, among them Web Portals. Through them, organizations develop their businesses in a

really 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. Our aim is to develop a data quality model for web

portals focused -oin three aspects: data quality expectations of data consumer, the software functionality of

web portals and the web data quality attributes recompiled from a literature review. In this paper, we will

present the first version of our model.

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.

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; Zhu and

Buchmann, 2002) or 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

(Gertz, Ozsu et al., 2004). However, there are not

works on DQ/IQ specifically developed for web

portals. As the literature shows that DQ/IQ is very

dependent on the context, we have centred our work

on the definition of a Data Quality Model for web

portals. To do so, we have used some works

developed for different contexts on the web but that

can be partially applied or adapted to our particular

context. For example, we have used the work of

Yang et al., (2004) where a quality framework for

web portals is proposed including data quality as a

part of it.

As the concept of “fitness for use” is widely

adopted in the literature (emphasizing the

importance of taking into consideration the

consumer viewpoint of quality), we have also

considered, for the definition of our model, the data

consumer viewpoint.

325

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

TOWARDS A DATA QUALITY MODEL FOR WEB PORTALS - Research in Progress.

In Proceedings of WEBIST 2006 - Second International Conference on Web Information Systems and Technologies - Internet Technology / Web

Interface and Applications, pages 325-331

DOI: 10.5220/0001242703250331

 SciTePress

To produce our model, we defined a four-stage

process, as set out in figure 1. In the first of these

phases, we recompiled web data quality attributes

from the literature and which we believe should

therefore be applicable to web portals. In the second

stage we built a matrix for the classification of the

attributes obtained in stage 1. This matrix reflects

two basic aspects considered in our model: the data

consumer perspective (by means data quality

expectations of data consumers on Internet) and the

basic functionalities which a data consumer uses to

interact with a Web portal.

Then in our third stage we used the matrix that

has been produced, to analyse the applicability of

each attribute of Web quality in a Web portal.

Finally, in the fourth stage, we will validate our

preliminary model, using surveys carried out on the

data consumers of a given portal.

In this paper we describe the first version of our

model, product of the three first stages of our

methodology. The structure of this paper is as

follows. In section 2, the components of our model

are presented. In section 3, we will deeply describe

the first version of our DQ/IQ Web Portal Model.

Finally, in section 4 we will conclude with our

general remarks and future work.

2 MODEL COMPONENTS

Web Portals are emerging Internet-based

applications that enable access to different sources

(providers) through a single interface (Mahdavi,

Shepherd et al., 2004). The primary objective of a

portal software solution is to create a working

environment where users can easily navigate in

order to find the information they specifically need

to perform their operational or strategic functions

quickly as well as to make decisions (Collins, 2001),

being responsibility of web portals’ owners the

achievement and maintenance of a high information

quality state (Kopcso, Pipino et al., 2000).

In this section, we will present the three basic

aspects considerate to define our DQ/IQ model for

web portals: the DQ/IQ attributes defined in the web

context, the data consumer expectations about data

quality, and web portals functionalities.

2.1 Data Consumer Expectations

When data management is conceptualized as a

production process (Strong, Lee et al., 1997), we can

identify three important roles in this process: (1)

data producers (who generate data), (2) data

custodians (who provide and manage resources for

processing and storing data), and (3) data consumers

(who access and use data for their tasks).

As in the context of web-based information

systems, roles (1) and (2) can be developed by the

same entity (Gertz, Ozsu et al., 2004), for web

portals context we identify two roles in the data

management process: (1) data producers-custodians,

and (2) data consumers.

So far, except for few works in DQ/IQ area, like

(Wang and Strong, 1996; Strong, Lee et al., 1997;

Burgess, Fiddian et al., 2004; Cappiello, Francalanci

et al., 2004), most of the works on the subject have

looked at quality from the data producer-custodian

perspective. The data consumer’s perspective of

quality differs from this in two important ways

(Burgess, Fiddian et al., 2004):

Data consumer has no control over the quality of

available data.

The aim of consumers is to find data that match

their personal needs, rather than provide data that

meet the needs of others.

Our proposal of a DQ/IQ model for web portals

considers the data quality expectations of data

consumer because, at the end, it is the consumer who

will judge whether a data is fitted for use or not

(Wang and Strong, 1996).

We will use the quality expectations of the data

consumer on the Internet, proposed in (Redman,

2001). These expectations are organized into six

categories: Privacy, Content, Quality of values,

Presentation, Improvement, and Commitment.

2.2 Web Portal Functionalities

A web portal is a system of data manufacturing

where we can distinguish the two roles established

in the previous subsection. Web portals present

basic software functionalities to data consumer

deploying their tasks and under our perspective, the

consumer judges data by using the application

functionalities. So, we used the web portal software

Figure 1: Stages in the development our model.

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326

functions that Collins proposes in (Collins, 2001)

considering them as basics in our model. These

functions are as follows: Data Points and

Integration, Taxonomy, Search Capabilities, Help

Features, Content Management, Process and Action,

Collaboration and Communication, Personalization,

Presentation, Administration, and Security. Behind

these functions, the web portal encapsulates the

producer-custodian role. Figure 2 illustrates this

fact.

2.3 Web DQ Revision

By using a DQ/IQ framework, organizations are able

to define a model for data, to identify relevant

quality attributes, to analyze attributes within both

current and future contexts, to provide a guide to

improve DQ/IQ and to solve data quality problems

(Kerr and Norris, 2004). In the literature, we have

found some proposals oriented to DQ/IQ on the web.

Among them, we can highlight those showed in

table 1. Related to such proposals, we can conclude

that there is no agreement concerning either the set

of attributes or, in several cases, their meaning. This

situation, probably, is a consequence of the different

domains and author’s focus of the studied works.

However, from this revision we captured several

data quality attributes. The most considered are (we

present between brackets different terms used for the

same concept): Accuracy (Accurate), in 60% of the

works; Completeness, in 50% of the works and

Timeliness (Timely), in 40% of the works; Concise

(Concise representation), Consistent (Consistent

representation), Currency (Current), Interpretability,

Relevance, Secure (Security), in 30% of the studies.

Accessibility (Accessible), Amount of data

(Appropriate amount of information), Availability,

Credibility, Objectivity, Reputation, Source

Reliability, Traceability (Traceable), Value added

are stated in 20% of the works.

Finally, Applicable, Clear, Comprehensive,

Confidentiality, Content, Convenient, Correct,

Customer Support, Degree of Duplicates, Degree of

Granularity, Documentation, Understand ability

(Ease of understanding), Expiration, Flexibility,

Freshness, Importance, Information value,

Maintainable, Novelty, Ontology, Pre-decision

availability, Price, Reliability, Response time,

Layout and design, Uniqueness, Validity, and

Verifiability are only studied in 10 % of the works

Summarizing the above-mentioned attributes, by

means of similarity in their names and definitions,

we have obtained a set of 28 attributes. Based on

these DQ/IQ attributes we will try to identify which

ones are applicable to the web portals context by

classifying them into the matrix construed by the

previous aspects (data consumer expectations x

functionalities).

3 RELATIONSHIPS BETWEEN

THE COMPONENTS OF THE

MODEL

Based on the previous background, we will

determine the relationship between the web portal

functionalities and the quality expectations of data

consumers. Then, we will present the definition of

each function according to (Collins, 2001) and we

will show their relationships (see figure 3).

Data Points and Integration. They provide the

ability to access information from a wide range of

internal and external information sources and

display the resulting information at the single point-

of-access desktop. The expectations applied to this

functionality are: Content (Consumers need a

description of portal areas covered, use of published

data, etc.), Presentation (formats, language, and

others are very important for easy interpretation) and

Improvement (users want to participate with their

opinions in the portal improvements knowing the

result of applying them).

Taxonomy. It provides information context

(including the organization-specific categories that

reflect and support organization’s business), we

consider that the expectations of data consumer

Figure 2: Roles in web portals.

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327

Table 1: Summary of web DQ/IQ framework in the literature.

Author Domain Framework structure

(Katerattanakul and Siau, 1999) Personal web sites 4 categories and 7 constructors

(Naumann and Rolker, 2000) Data integration 3 classes and 22 of quality criterion

(Aboelmeged, 2000) e-commerce 7 stages to modelling DQ problems

(Katerattanakul and Siau, 2001) e-commerce 4 categories associated with 3 categories of data

user requirements.

(Pernici and Scannapieco,

2002)

Web information

systems (data evolution)

4 categories, 7 activities of DQ design and

architecture to DQ management.

(Fugini, Mecella et al., 2002) e-service

cooperative

8 dimensions

(Graefe, 2003) Decision making 8 dimensions and 12 aspects related to

(providers/consumers)

(Eppler, Algesheimer et al.,

2003)

Web sites 4 dimensions and 16 attributes

(Gertz, Ozsu et al., 2004) DQ on the web 5 dimensions

(Moustakis, Litos et al., 2004) Web sites 5 categories and 10 sub-categories

(Melkas, 2004) Organizational

networks

6 stages to DQ analysis with several dimensions

associated with each one

(Bouzeghoub and Peralta, 2004) Data integration 2 factors and 4 metrics

(Yang, Cai et al., 2004) Web information

portals

2 dimensions

are: Content (consumers need a description of

which data are published and how they should be

used, easy-to-understand definitions of every

important term, etc.), Presentation (formats and

language in the taxonomy are very important for

easy interpretation, users should expect to find

instructions when reading the data), and

Improvement (user should expect to convey his/her

comments on data in the taxonomy and know the

result of improvements).

Search Capabilities. It provides several services

for web portal users and needs searches across the

enterprise, World Wide Web, and search engine

catalogs and indexes. The expectations applied to

this functionality are: Quality of values (Data

consumer should expect that the result of searches is

correct, current and complete), Presentation

(formats and language are important for consumers,

for the search and for easy interpretation of results)

and Improvement (consumer should expect to

convey his/her comments on data in the taxonomy

and know the result of improvements).

Help Features. They provide help when using

the web portal. The expectations applied to this

functionality are: Presentation (formats, language,

and others are very important for easy interpretation

of help texts) and Commitment (consumer should be

easily able to ask and obtain answer to any question

regarding the proper use or meaning of data, update

schedules, etc.).

Content Management. This function supports

content creation, authorization, and inclusion in (or

exclusion from) web portal collections. The

expectations applied to this functionality are:

Privacy (it should exist privacy policy for all

consumers to manage, to access sources and to

guarantee web portals data), Content (consumers

need a description of data collections, that all data

needed for an intended use are provided, etc.),

Quality of values (consumer should expect that all

data values are correct, current and complete, unless

otherwise stated), Presentation (formats and

language should be appropriate for easy

interpretation), Improvement (consumer should

expect to convey his/her comments on contents and

their management and know the result of the

improvements) and Commitment (consumer should

be easily able to ask and have any question

regarding the proper use or meaning of data, update

schedules, etc. answered).

Process and Action. This function enables the

web portal user to initiate and participate in a

business process of portal owner. The expectations

applied to this functionality are: Privacy (Data

consumer should expect that there is a privacy

policy to manage the data about the business on the

portal), Content ( Consumers should expect to find

descriptions about the data published for the

processes and actions, appropriate and inappropriate

uses, that all data needed for the process and actions

are provided, etc.), Quality of values (that all data

associated to this function are correct, current and

complete, unless otherwise stated), Presentation

(formats, language, and others are very important for

properly interpret data), Improvement (consumer

should expect to convey his/her comments on

contents and their management and know the result

of improvements) and Commitment (consumer

WEBIST 2006 - WEB INTERFACES AND APPLICATIONS

328

should be easily able to ask and to obtain answer to

any questions regarding the proper use or meaning

of data in a process or action, etc.).

Collaboration and Communication. This

function facilitates discussion, locating innovative

ideas, and recognizing resourceful solutions. The

expectations applied to this functionality are:

Privacy (consumer should expect privacy policy for

all consumers that participate in activities of this

function), and Commitment (consumer should be

easily able to ask and have any questions regarding

the proper use or meaning of data for the

collaboration and/or communication, etc.,

answered).

Personalization. This is a critical component to

create a working environment that is organized and

configured specifically to each user. The

expectations applied to this functionality are:

Privacy (consumer should expect privacy and

security about their personalization data, profile,

etc.), and Quality of values ( data about user profile

should be correct, current).

Presentation. It provides both the knowledge

desktop and the visual experience to the web portal

user that encapsulates all of the portal’s

functionality. The expectations applied to this

functionality are: Content (the presentation of a web

portal should include data about covered areas ,

appropriate and inappropriate uses, definitions,

information about the sources, etc.), Quality of

values (the data of this function should be correct,

current and complete.), Presentation (formats,

language, and others are very important for easy

interpretation and appropriate use of portals data.)

and Improvement (consumer should expect to

convey his/her comments on contents and their

management and know the result of the

improvements).

Administration. This function provides service

for deploying maintenance activities or tasks

associated with the web portal system. The

expectations applied to this functionality are:

Privacy ( Data consumers need security for data

about the portal administration) and Quality of

values (Data about tasks or activities of

administration should be correct and complete).

Security. It provides a description of the levels of

access that each user or groups of users are allowed

for each portal application and software function

included in the web portal. The expectations applied

to this functionality are: Privacy (consumer need

of data consumers.), Quality of values (data about

the levels of access should be correct and current.)

and Presentation (data about security should be in

format and language for easy interpretation).

Concerning the relationships established in the

matrix of figure 3, we can remark that Presentation

is the category of data consumer expectation with

more relations. This perfectly fits with the main goal

of any web applications, which is to be useful and

user-friendly for any kind of user.

The next step is to fill in each cell of the matrix

with Web DQ/IQ attributes obtained from the study

presented in 2.3. As a result of this, we have a subset

of DQ/IQ attributes that can be used in a web portal

to evaluate data quality. In table 2, we will show the

most relevant attributes for each category of data

consumer expectations.

To validate and complete this assignation we

plan to work with portal data consumers through

surveys and questionnaires. Once the validation is

finished, we will reorganize the attributes obtaining

the final version of our model.

4 CONCLUSIONS AND FUTURE

WORK

The great majority of works found in the literature

show that data quality or information quality 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. However, in the web

portal context, data quality frameworks do not exist

In this paper, we have presented a proposal that

combines three aspects: (1) a set of web data quality

attributes resulting from a data quality literature

survey that can be applicable and useful for a web

portal, (2) the data quality expectations of data

consumer on the Internet, and (3) the basic

functionalities for a web portal. These aspects have

been related by obtaining a first set of data quality

Figure 3: Matrix stating the relationships between dat

consumer expectations and web portal functionalities.

TOWARDS A DATA QUALITY MODEL FOR WEB PORTALS - Research in Progress

329

Table 2: Web Data Quality attributes applied to web portal functionalities in each category.

Category of

Data Consumer

Expectations

Web portal functionalities related

to each category

Web DQ/IQ attributes applying almost one

functionality in each category

Privacy Content management

Process and actions

Collaboration and Communication

Personalization

Administration

Security

Content Data Points and Integration

Taxonomy

Content management

Process and actions

Presentation

Accessibility, Currency, Amount of data,

Understandability, Relevance, Concise Representation,

Validity, Traceability, Completeness, Reliability,

Credibility, Timeliness, Availability, Documentation,

Specialization, Interpretability, Easy to use

Quality of

data

Data Points and Integration

Search Capabilities

Content management

Process and actions

Personalization

Presentation

Security

Accessibility, Currency, Amount of data,

Credibility, Understandability, Accuracy, Expiration,

Novelty, Relevance, Validity, Concise Representation,

Completeness, Reliability, Availability, Documentation,

Duplicity, Specialization, Interpretability, Objectivity,

Relevance, Reputation, Traceability, Utility, Value-

added, Easy to use

Presentation Data Points and Integration

Taxonomy

Search Capabilities

Help Features

Content management

Process and actions

Collaboration and Communication

Presentation

Administration

Security

Amount of data, Completeness, Understandability,

Easy to use, Concise Representation, Consistent

Representation, Validity, Relevance, Interpretability,

User support, Availability, Specialization, Flexibility

Improvement Data Points and Integration

Taxonomy

Search Capabilities

Content management

Process and actions

Presentation

Accessibility, Reliability, Credibility,

Understandability, User support, Traceability

Commitment Help Features

Content management

Process and actions

Accessibility, Reliability, User support,

attributes for the different data consumer

expectations X functionalities.

Our future work, now in progress, consists of

validating and refining this model. First of all, it is

necessary to check these DQ/IQ attributes with data

consumers in a web portal. We plan to make a

questionnaire for each web portal functionality.

Then, once we have validated the model, we will

define a framework including the necessary

elements to evaluate a DQ/IQ in a web portal. Our

aim is to obtain a flexible framework where the data

consumer can select the attributes used to evaluate

the quality of data in a web portal, depending on the

existing functionalities and their personal data

quality expectations.

ACKNOWLEDGEMENTS

This research is part of the following projects:

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

Dirección General de Investigación of the 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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