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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Lorvão Antunes, A. , Cardoso, E. & Barateiro, J. (2022). Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review. International Journal of Information Management Data Insights. 2 (2)
Exportar Referência (IEEE)
A. L. Antunes et al.,  "Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review", in Int. Journal of Information Management Data Insights, vol. 2, no. 2, 2022
Exportar BibTeX
@article{antunes2022_1728385553062,
	author = "Lorvão Antunes, A.  and Cardoso, E. and Barateiro, J.",
	title = "Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review",
	journal = "International Journal of Information Management Data Insights",
	year = "2022",
	volume = "2",
	number = "2",
	doi = "10.1016/j.jjimei.2022.100131",
	url = "https://www.sciencedirect.com/science/article/pii/S266709682200074X?via%3Dihub"
}
Exportar RIS
TY  - JOUR
TI  - Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review
T2  - International Journal of Information Management Data Insights
VL  - 2
IS  - 2
AU  - Lorvão Antunes, A. 
AU  - Cardoso, E.
AU  - Barateiro, J.
PY  - 2022
SN  - 2667-0968
DO  - 10.1016/j.jjimei.2022.100131
UR  - https://www.sciencedirect.com/science/article/pii/S266709682200074X?via%3Dihub
AB  - Semantic Web (SW) techniques, such as ontologies, are used in Information Systems (IS) to cope with the growing need for sharing and reusing data and knowledge in various research areas. Despite the increasing emphasis on unstructured data analysis in IS, structured data and its analysis remain critical for organizational performance management. This systematic literature review aims at analyzing the incorporation and impact of ontologies in Data Warehouse/Business Intelligence (DW/BI) systems, contributing to the current literature by providing a classification of works based on the field of each case study, SW techniques used, and the authors’ motivations for using them, with a focus on DW/BI design, development and exploration tasks. A search strategy was developed, including the definition of keywords, inclusion and exclusion criteria, and the selection of search engines. Ontologies are mainly defined using the Ontology Web Language standard to support multiple DW/BI tasks, such as Dimensional Modeling, Requirement Analysis, Extract-Transform-Load, and BI Application Design. Reviewed authors present a variety of motivations for ontology-driven solutions in DW/BI, such as eliminating or solving data heterogeneity/semantics problems, increasing interoperability, facilitating integration, or providing semantic content for requirements and data analysis. Further, implications for practice and research agenda are indicated.
ER  -