Multidimensional Design by Examples

Romero, Óscar; Abelló, Alberto

doi:10.1007/11823728_9

Cited by 32 publications

(24 citation statements)

References 6 publications

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“…Automated conceptual multidimensional modelling can be classified into three approaches based on how they are obtained: supply-driven, demand-driven and hybrid (a mix of both supply-driven and demand driven) approaches. Supply-driven approach considers only the schema and the ontology of the data sources to obtain a multidimensional data model, whereas demand-driven (Romero, 2006) and (Romero, 2008) and takes into consideration the user queries to obtain the final model.…”

Section: User-centric Multidimensional Data Analysismentioning

confidence: 99%

Heterogeneous Sensor Data Exploration and Sustainable Declarative Monitoring Architecture: Application to Smart Building

Servigne

Gripay

Pinarer

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Concerning energy consumption and monitoring architectures, our goal is to develop a sustainable declarative monitoring architecture for lower energy consumption taking into account the monitoring system itself. Our second is to develop theoretical and practical tools to model, explore and exploit heterogeneous data from various sources in order to understand a phenomenon like energy consumption of smart building vs inhabitants' social behaviours. We focus on a generic model for data acquisition campaigns based on the concept of generic sensor. The concept of generic sensor is centered on acquired data and on their inherent multidimensional structure, to support complex domain-specific or field-oriented analysis processes. We consider that a methodological breakthrough may pave the way to deep understanding of voluminous and heterogeneous scientific data sets. Our use case concerns energy efficiency of buildings to understand relationship between physical phenomena and user behaviors. The aim of this paper is to give a presentation of our methodology and results concerning architecture and user-centric tools.

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Section: User-centric Multidimensional Data Analysismentioning

confidence: 99%

Heterogeneous Sensor Data Exploration and Sustainable Declarative Monitoring Architecture: Application to Smart Building

Servigne

Gripay

Pinarer

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Finally, this approach uses the same criteria as (Romero & Abelló, 2006) to validate the multidimensional schema.…”

Section: Song Et Al (2007)mentioning

confidence: 99%

A Survey of Multidimensional Modeling Methodologies

Romero

Abelló

2009

International Journal of Data Warehousing and Mining

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“…Además, esta propuesta no se basa en estándares, lo que podría afectar a su aplicabilidad. La propuesta presentada en [22] automatiza la identificación en las fuentes de datos de conceptos MD relacionados con requisitos de usuario. No obstante, esta propuesta parte de la base de que los usuarios pueden expresar fácilmente sus requisitos de información como sentencias SQL, lo que puede no ser cierto cuando las fuentes operacionales son complejas.…”

Section: Trabajos Relacionadosunclassified

Model-driven reverse engineering for data warehouse design

Mazón

Trujillo

2008

IEEE Latin Am. Trans.

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Abstract-Data warehouses integrate several operational sources to provide a multidimensional analysis of data, thus improving the decision making process. Therefore, an in-depth analysis of these data sources is crucial for data warehouse development. Traditionally, this analysis has been based on a set of informal guidelines or heuristics to support the manually discovery of multidimensional elements on a well-known documentation. Therefore, this task may become highly tedious and prone to fail. In this paper, MDA (Model Driven Architecture) is used to design a reverse engineering process in which the following tasks are performed (i) obtain a logical representation of data sources (ii) mark this logical representation with multidimensional concepts, and (iii) derive a conceptual multidimensional model from the marked model.

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Multidimensional Design by Examples

Cited by 32 publications

References 6 publications

Heterogeneous Sensor Data Exploration and Sustainable Declarative Monitoring Architecture: Application to Smart Building

Heterogeneous Sensor Data Exploration and Sustainable Declarative Monitoring Architecture: Application to Smart Building

A Survey of Multidimensional Modeling Methodologies

Model-driven reverse engineering for data warehouse design

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