Selma Khouri

A methodology and tool for conceptual designing a data warehouse from ontology-based sources

Ontologies become more popular in various domains. In database, they contribute largely in designing operational databases, that we call ontology-based databases (OBDB). An OBDB stores ontology and their instances in the same repository. Several DBMS propose solutions to manipulate and query this type of databases. As consequence, these operational OBDB become a candidate to feed data warehouses (DW). In this paper, we propose a new conceptual design methodology of DW from data residing in various OBDB that takes into account sources and decision maker requirements. As the result, a semantic DW model is generated. The presence of ontology within a DW facilitates its querying in semantic level and its future integration with other DW built using our methodology. Finally, we present a case tool, called S2RWC, supporting our proposal.

Towards a conceptualization of ETL and physical storage of semantic data warehouses as a service

The data warehouse technology has become the incontestable tool for businesses and organizations to make strategic decisions to ensure their competitively. The construction of a data warehouse (

Semantic Data Warehouse Design: From ETL to Deployment à la Carte

\mathcal{D}\mathcal{W}

DWOBS: data warehouse design from ontology-based sources

) passes by selecting relevant information sources, extracting relevant data and loading them into the

Requirements Driven Data Warehouse Design: We Can Go Further

\mathcal{D}\mathcal{W}

Efficient, Unified, and Intelligent User Requirement Collection and Analysis in Global Enterprises

. These processes require a precise expertise from designers related to logical and physical implementations of information sources, which is not usually an easy task. The diversity and heterogeneity of information sources makes the construction process of the

Generic Methodology for Semantic Data Warehouse Design: From Schema Definition to ETL

\mathcal{D}\mathcal{W}

CiDHouse: Contextual SemantIc Data WareHouses

complex and time consuming. Domain ontologies have been proposed to reduce heterogeneity between sources, platforms, services, etc. They resolve syntax and semantic conflicts. The phenomenon of adopting domain ontologies by organizations creates a new type of databases, called semantic databases (

More Investment in Conceptual Designers: Think about it!

\mathcal{S}\mathcal{D}\mathcal{B}

Tracing data warehouse design lifecycle semantically

). As a consequence, they become a candidate for building the semantic