Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

Generación asistida por computadoras de modelos de almacenes de datos: análisis de la información

En este trabajo se presentan las pautas metodológicas para la generación asistida por computadoras de modelos de almacenes de datos (AD), estas pautas metodológicas se dividen en 4 etapas, las 3 etapas primeras son: análisis de la información, modelo conceptual y diseño lógico y una que ocurre dentro de cada una de las etapas anteriores que es denominada etapa de trazabilidad. Estas etapas describen cómo podemos obtener a partir de los sistemas operacionales heredados (E/R) una propuesta de modelado de almacenes de datos. Debido a que el análisis de la información juega un papel fundamental en las etapas tempranas, en este trabajo se profundiza en la primera etapa de estas pautas metodológicas. En la primera etapa se trabaja en dos fases una para la selección de los requisitos de usuario y otra para el trabajo con los esquemas OLTP

Conceptual modeling research in information systems: What we now know and what we still do not know

Much of conceptual modeling research over recent times has been guided by a seminal research agenda developed by Wand and Weber (2002), which identified twenty-two research opportunities. In this paper, we explore whether existing research has provided sufficient answers to these questions. Our findings from a review of the literature show a dialectic: several of the opportunities noted in 2002 have been addressed substantially while others have been entirely neglected. We also found several path breaking studies that addressed problems not spotted by the initial framework. To stimulate a forward-looking wave of conceptual modeling research, we provide a new framework that draws the attention of conceptual modeling research to the interplay between digital representations and outcomes