Session:

Knowledge Representation, Decision Support and Expert Systems
Tuesday, March 02, 2004, 17.35 – 17.55

Session Chair:
Vice Chair:

A. Dobnikar
M. Savoji

Paper Title:

Abnormal Data Formats Identification and Resolution on Data Warehousing Populating Process

Author(s):

Dr A. Lourenço, Universidade do Minho, Portugal
Prof. O. Belo, University of Minho, Portugal

Abstract:

Data Warehousing systems are perhaps one of the most valuable assets that organisations possess today. They manage and sustain crucial, strategic information, granting the urging decision support. However, before taking advantage of this magnificent resource, there has to be set a plan to ensure its population. The process of extracting, transforming and loading data into the data warehouse is anything less straightforward. These scenarios are inherently heterogeneous. The idea of gathering every piece of information that is available and thought useful brings along different data models and data schemas to conciliate. Besides, within each single source, it is likely that several kinds of conflicts, inconsistencies and errors pump up. Therefore, tools capable of identifying and resolving these situations are in order. This paper aims to bring some light into the subject, covering basic issues related with data cleaning, as well as, proposing a new computational platform - an agent-based abnormal data formats identification and resolution platform. The aim was set on assisting the process, learning from past experiences and thus, evolving wrappers knowledge about abnormal situations’ resolution. Eventually, this evolving will enhance the data warehouse population process, enlarging the integrated volume of data and enriching its actual quality and consistency.

KEYWORDS: Data Warehousing systems, data cleaning and integration, agent-based systems, FIPA, JADE, and Knowledge Discovery in Databases.