A Survey of Multidimensional Modeling Methodologies

Romero, Óscar; Abelló, Alberto

doi:10.4018/jdwm.2009040101

Cited by 83 publications

(49 citation statements)

References 17 publications

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“…The criteria used for this analysis can be summarized as follows: the role played by end-user requirements and data sources for each method, the degree of automation achieved and the quality of the output produced (i.e., which MD concepts and features do they really consider). The use of this criteria is justified by the conclusions drawn by a previous, exhaustive analysis of current design methods that can be found in [17].…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Framework on Multidimensional Modeling

Romero

Abelló

2011

Advances in Conceptual Modeling. Recent Developments and New Directions

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Abstract. In this paper we discuss what current multidimensional design approaches provide and which are their major flaws. Our contribution lays in a comprehensive framework that does not focus on how these approaches work but what they do provide for usage in real data warehouse projects. So that, we do not aim at comparing current approaches but set up a framework (based on four criteria: the role played by enduser requirements and data sources, the degree of automation achieved and the quality of the output produced) highlighting their drawbacks, and the need for further research on this area.

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Section: Introductionmentioning

confidence: 99%

A Comprehensive Framework on Multidimensional Modeling

Romero

Abelló

2011

Advances in Conceptual Modeling. Recent Developments and New Directions

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“…Although the authors of "Ref. [27,28,29]" had used queries for requirements collection, but they did not take into To the best of our knowledge, there has not been a data warehouse design study based on fuzzy ontology and taking into account the imprecision at the requirements analysis phase and where the requirements are expressed in query form.…”

Section: A Decisional Requirements Analysis and Imprecision Treatmentmentioning

confidence: 99%

Fuzzy Ontology-based Approach for the Requirements Query Imprecision Assessment in Data Warehouse Design Process near Negative Fuzzy Operator

Abdelmadjid¹,

Malki²,

Boukhalfa³

et al. 2018

IJITCS

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Abstract-The vagueness in decision-making may be due to ambiguity in the decisional requirements expression. Therefore, in the literature dealing with vagueness in decision systems, studies were concentrated on data vagueness and not on decision requirements. In order to evaluate the expression in decision-making requirements and in order to improve the data warehouses design quality, this paper presents a rigorous fuzzy ontologybased solution.Based on the latest Zadeh theory "Ref.[1]", Authors in "Ref. [2.3]", propose a solution consisting in using ontologies to provide "an understanding of how the meaning of a proposal can be composed of the meaning of its constituents. One of the limitations of this solution is the fuzziness presence only at the adjective sentence. In some sense, our proposal can be seen as a continuation of that work. We limit our study, in this paper to the "Near negative" operator case. To the best of our knowledge, this case has not been addressed yet in the data warehouse context.

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“…Level-Level association roles, multiplicities, default: many-to-one Level-Level generalization default: disjoint and complete Fact-Dimension association multiplicities, default: many-to-one houses and [36] provides a summary about general multidimensional modeling methodologies), our paper presents the first survey about summarizability issues in multidimensional modeling.…”

Section: Construct Featuresmentioning

confidence: 99%

A survey on summarizability issues in multidimensional modeling

Mazón

Lechtenbörger

Trujillo

2009

Data & Knowledge Engineering

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The development of a data warehouse (DW) system is based on a conceptual multidimensional model, which provides a high level of abstraction in accurately and expressively describing real-world situations. Once this model is designed, the corresponding logical representation must be obtained as the basis of the implementation of the DW according to one specific technology. However, even though a good conceptual multidimensional model is designed underneath a DW, there is a semantic gap between this model and its logical representation. In particular, this gap complicates an adequate treatment of summarizability issues, which in turn may lead to erroneous results of data analysis tools. Research addressing this topic has produced only partial solutions, and individual terminology used by different parties hinders further progress. Consequently, based on a unifying vocabulary, this survey sheds light on (i) the weak and strong points of current approaches for modeling complex multidimensional structures that reflect real-world situations in a conceptual multidimensional model and (ii) existing mechanisms to avoid summarizability problems when conceptual multidimensional models are being implemented.

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A Survey of Multidimensional Modeling Methodologies

Abstract: words or less[Article copies are available for purchase from InfoSci-on-Demand.com]

Cited by 83 publications

References 17 publications

A Comprehensive Framework on Multidimensional Modeling

A Comprehensive Framework on Multidimensional Modeling

Fuzzy Ontology-based Approach for the Requirements Query Imprecision Assessment in Data Warehouse Design Process near Negative Fuzzy Operator

A survey on summarizability issues in multidimensional modeling

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