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Ontology-Based Conceptual Design of ETL Processes for Both Structured and Semi-Structured Data

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  • Dimitrios Skoutas

    (National Technical University of Athens, Greece)

  • Alkis Simitsis

    (National Technical University of Athens, Greece)

Abstract

One of the main tasks in the early stages of a data warehouse project is the identification of the appropriate transformations and the specification of inter-schema mappings from the data sources to the data warehouse. In this article, we propose an ontology-based approach to facilitate the conceptual design of the back stage of a data warehouse. A graph-based representation is used as a conceptual model for the datastores, so that both structured and semi-structured data are supported and handled in a uniform way. The proposed approach is based on the use of Semantic Web technologies to semantically annotate the data sources and the data warehouse, so that mappings between them can be inferred, thereby resolving the issue of heterogeneity. Specifically, a suitable application ontology is created and used to annotate the datastores. The language used for describing the ontology is OWL-DL. Based on the provided annotations, a DL reasoner is employed to infer semantic correspondences and conflicts among the datastores, and to propose a set of conceptual operations for transforming data from the source datastores to the data warehouse.

Suggested Citation

  • Dimitrios Skoutas & Alkis Simitsis, 2007. "Ontology-Based Conceptual Design of ETL Processes for Both Structured and Semi-Structured Data," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 3(4), pages 1-24, October.
  • Handle: RePEc:igg:jswis0:v:3:y:2007:i:4:p:1-24
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    Cited by:

    1. Asma Dhaouadi & Khadija Bousselmi & Mohamed Mohsen Gammoudi & Sébastien Monnet & Slimane Hammoudi, 2022. "Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons," Data, MDPI, vol. 7(8), pages 1-38, August.
    2. Petar Jovanovic & Sergi Nadal & Oscar Romero & Alberto Abelló & Besim Bilalli, 0. "Quarry: A User-centered Big Data Integration Platform," Information Systems Frontiers, Springer, vol. 0, pages 1-25.
    3. Petar Jovanovic & Sergi Nadal & Oscar Romero & Alberto Abelló & Besim Bilalli, 2021. "Quarry: A User-centered Big Data Integration Platform," Information Systems Frontiers, Springer, vol. 23(1), pages 9-33, February.
    4. Jianhui Chen & Ning Zhong & Jianhua Feng, 2017. "Developing a Provenance Warehouse for the Systematic Brain Informatics Study," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1581-1609, November.

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