and trained in Information Quality Management
principles, and especially in the information quality
dimensions as outlined in table 1.
Given that the sites under review were among
large quoted companies, small quoted companies,
charities and not for profit, statutory and unquoted
organisations, some of which had been recognised
for excellence in financial reporting, it was
surprising to find that 81% of the sites under
examination failed on the basic input validation. One
Hundred percent of large and small quoted
companies failed in their email input validation
while 67% of charities/not for profit organisations
and statutory and unquoted organisations failed to
validate emails. No less than 90% of all
organisations under review failed to provide a useful
search engine and only 71 % provided a site map.
However, 67% provided a site search facility and
81% had friendly URL’s and most sites had good
design layout that was consistent throughout making
it easier for the user to navigate.
Many problems could be eliminated by checking
for letters (alphabet entries only); numbers (
numeric entries only); a valid range of values; a
valid date input; and valid email addresses. Keeping
in mind that a user could enter a valid e-mail address
that does not actually exist it is imperative that some
sort of activation process needs to be done in order
to confirm a valid and correct email address.
REFERENCES
Beckford John, 2nd edition, Quality, Rutledge Taylor and
Frances Group, London and New York (2005)
Bugajski Joseph, Grossman Robert L., Tang Zhao, An
event based framework for improving information
quality that integrates baseline models, casual models
and formal models, IQIS 2005 ACM 1-59593-160-
0/5/06. (2005)
Fraternali, P., Tools and Approaches for Developing Data-
Intensive Web Applications: A Survey, ACM
Computing Surveys, vol.31, No.3, (1999)
Internet_World_Statistics
http://www.internetworldstats.com
Kumar Giri, Ballou Tayi, Ballou Donald, P., Guest editors,
Examining data Quality, Communications of the
ACM, vol. 41, No 2, pp 54-57. (1998)
Mandel Theo, Quality Technical Information: Paving the
Way for UsableW3C Web Content Accessibility
Guidelines 1.0, \\http://www.w3.org/tr/wai-
webcontent/
Olson Jack E Data Quality: The Accuracy Dimension,
Morgan Kaufmann, ISBN 1558608915. (2003)
Open Web Application Security Project,
http://umn.dl.sourceforge.net/sourceforge/owasp/OW
ASPTopTen2004.pdf
Orr Ken, Data Quality and Systems, Communications of
the ACM, vol. 41, No 2, pp 66-71, (1998)
Pike R.J., Barnes R TQM in Action: a practical approach
to continuous performance improvement, 1996,
Springer, ISBN 0412715309
Print and Web Interface Design, ACM Journal of
Computer Documentation, vol. 26, No. 3. (2002)
Redmond, Thomas C, Improve Data Quality for
Competitive Advantage, Sloan Management Review,
vol 36, no 2, pp. 99-107 (1995)
Strong, Dianne M., Lee Yang W., Wang Richard Y., Data
Quality in Context Communications of the ACM, vol.
40, No 5, pp 103-109. (1997)
Stylianou Antonis C., Kumar Ram L, An integrative
framework for IS Quality management,
Communications of the ACM, vol. 43, No 9, pp 99-
104. (2000)
Tauscher, L., Greenberg, S., How people revisit web
pages: Empirical findings and implication for the
design of history systems, International Journal of
Human-Computer Studies, 47, 97-137 (1997)
Wang Richard Y., and Strong, D.M. Beyond accuracy:
what data quality means to data consumers, Journal of
Management Information Systems 12, (4), pp 5–34.
(1996)
Wang Richard Y., A product perspective on Total Data
Quality Management, Communications of the ACM,
vol.41, No.2, pp58-65. (1998)
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