A global and comprehensive approach for XML data warehouse design

Ouaret, Zoubir; Boussaïd, Omar; Chalal, Rachid

doi:10.1109/aiccsa.2014.7073251

Cited by 1 publication

(2 citation statements)

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“…Further the work has been extended to design multiple cubes [8] of multidimensional model from XML schema. A semi-automatic approach [9] was proposed for XML data warehouse design starting from XML schemas as data sources. It generates numbers of UML class diagram from XML schema and then the numbers of classes are reduced using a set of rules.…”

Section: Hementioning

confidence: 99%

“…It generates numbers of UML class diagram from XML schema and then the numbers of classes are reduced using a set of rules. Finally a multi-dimensional (MD) element extraction algorithm [9] is used to automatically identify facts, measures and their corresponding dimensions. An automatic approach for designing the logical schema for a data mart starting from the XML schema describing XML sources using UML and QVT transformation language was described in [10].…”

Section: Hementioning

confidence: 99%

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ROLAP based data warehouse schema to XML schema conversion

Sen

Cortesi

Chaki³

2016

2016 IEEE International Conference on Industrial Technology (ICIT)

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Abstract-Data Warehouse is one of the powerful tools for analytical processing. XML on the other hand is widely used to handle data in web environment. XML to data warehouse integration is a subject of interest for the business organization to use the semi-structured XML for analytical processing. However, in this research work we approached the problem in reverse direction. Here we generate equivalent XML schema from the existing data warehouse schema for an organization which does not has the XML platform to manage the web data. The proposed reverse engineering framework uses one of the existing methodologies of converting the XML schema to data warehouse schema. However, we have applied it in a reverse approach. Moreover we have established a formalism to prove the soundness and correctness of both the conversion mechanisms.

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Section: Hementioning

confidence: 99%

Section: Hementioning

confidence: 99%