: a multidimensional conceptual model extending UML

Abelló, Alberto; Samos, José; Saltor, Fèlix

doi:10.1016/j.is.2004.12.002

Cited by 131 publications

(124 citation statements)

References 26 publications

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“…Furthermore, these approaches do not provide enough expressivity to specify every complex multidimensional structure, thus only providing partial solutions. Hence, subsequent research dealt with the definition of more expressive multidimensional formalisms for defining real-world scenarios [19,1,33]. These approaches are based upon an object-oriented approach to allow designers to model more complex multidimensional structures, but they neither offer guidelines for using those more expressive features properly nor formal mechanisms to avoid summarizability problems of complex multidimensional models.…”

Section: Discussionmentioning

confidence: 99%

“…It is instructive to note, however, that this approach does not allow generalizations as modeling constructs. Moreover, although several multidimensional design proposals are based on object-oriented modeling and, in particular, the UML [1,19,33] none of them explicitly suggests the use of generalization to avoid roll-up incompleteness. In line with [3] we argue that optional constructs such multiplicities of "0" should be avoided in understandable conceptual models whenever possible.…”

Section: Generalizationmentioning

confidence: 99%

“…Afterwards, we consider the recent approaches [1,19,33], which exhibit more expressiveness based on an object-oriented perspective but which lack in a detailed proposal for ensuring summarizability.…”

Section: General Approaches For Multidimensional Modelingmentioning

confidence: 99%

“…Another approach which uses UML constructs is described in [1], where the authors define the multidimensional data model YAM 2 . Here, a dimension is a connected, directed graph, where every vertex corresponds to a hierarchy level, and an edge reflects that every instance of target level can be decomposed into a collection of instances of the source level (a relation between levels reflects a part-whole relationship among instances of levels).…”

Section: General Approaches For Multidimensional Modelingmentioning

confidence: 99%

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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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Section: Discussionmentioning

confidence: 99%

Section: Generalizationmentioning

confidence: 99%

Section: General Approaches For Multidimensional Modelingmentioning

confidence: 99%

Section: General Approaches For Multidimensional Modelingmentioning

confidence: 99%

See 2 more Smart Citations

A survey on summarizability issues in multidimensional modeling

Mazón

Lechtenbörger

Trujillo

2009

Data & Knowledge Engineering

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“…Now, we present a study of the best available conceptual and logical models for data warehousing. Existing conceptual modeling approaches can be broadly classified into Extensions of Entity Relationship (E/R) models ( [6][7][8][9][10]), Extensions of Unified Modeling Language (UML) ( [11][12][13]) and Ad-hoc ( [14][15][16][17]) design models. Several different logical models have also been proposed to model multidimensional data in the past few years.…”

Section: Related Workmentioning

confidence: 99%

On the Requirements for User-Centric Spatial Data Warehousing and SOLAP

Viswanathan

Schneider

2011

Lecture Notes in Computer Science

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Abstract. Data warehouses and OLAP systems help to analyze complex multidimensional data and provide decision support. With the availability of large amounts of spatial data in recent years, several new models have been proposed to enable the integration of spatial data in data warehouses and to help analyze such data. This is often achieved by a combination of GIS and spatial analysis tools with OLAP and database systems, with the primary goal of supporting spatial analysis dimensions, spatial measures and spatial aggregation operations. However, this poses several new challenges related to spatial data modeling in a multidimensional context, such as the need for new spatial aggregation operations and ensuring consistent and valid results. In this paper, we review the existing modeling strategies for spatial data warehouses and SOLAP in all three levels: conceptual, logical and implementation. While studying these models, we gather the most essential requirements for handling spatial data in data warehouses and use insights from spatial databases to provide a "meta-framework" for modeling spatial data warehouses. This strategy keeps the user as the focal point and achieves a clear abstraction of the data for all stakeholders in the system. Our goal is to make analysis more user-friendly and pave the way for a clear conceptual model that defines new multidimensional abstract data types (ADTs) and operations to support spatial data in data warehouses.

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Multidimensional Design by Examples

Romero

Abelló

2006

Data Warehousing and Knowledge Discovery

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: a multidimensional conceptual model extending UML

Cited by 131 publications

References 26 publications

A survey on summarizability issues in multidimensional modeling

A survey on summarizability issues in multidimensional modeling

On the Requirements for User-Centric Spatial Data Warehousing and SOLAP

Multidimensional Design by Examples

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