Bridging context and data warehouses through ontologies

Barkat, Okba; Khouri, Selma; Bellatreche, Ladjel; Boustia, Narhimene

doi:10.1145/3019612.3019838

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…In a similar way that Klarman and Gutiérrez-Basulto define a language for contexts, Barkat et al [21] separate the expression of context from the ontologies using a specific context language, which is formalized using a UML class diagram. This model makes use of external ontologies to express some elements of a context, such as temporal elements or units of measure.…”

Section: Expression Of Context In Ontologiesmentioning

confidence: 99%

Using Adaptive Logics for Expression of Context and Interoperability in DL Ontologies

2022

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Ontologies are logical theories that are used in computer science for describing different items such as web services, agents in multi-agent systems, or domain knowledge. Many ontologies exist, expressing various domains of knowledge with different abstraction levels (domain ontologies, top-level ontologies, and task ontologies are the usual categories). The conceptualization of the knowledge contained in an ontology is subject to change, whether because the context of its use changes, because the domain evolves, or because an ontology needs to interoperate with other elements using other ontologies. Change in logical theories is a form of defeasible reasoning, in which some formulas need to be added or removed from a knowledge base. Adaptive Logics (AL) is a logic managing defeasible reasoning that we investigate in this paper for managing change in ontologies expressed with Description Logics (DL). The adaptation of AL for DL will help express the context in which formulas remain valid or can be added to a DL knowledge base, and ease the interoperability between ontologies.

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Section: Expression Of Context In Ontologiesmentioning

confidence: 99%

Using Adaptive Logics for Expression of Context and Interoperability in DL Ontologies

2022

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“…On the other hand, Benslimane and colleague [17] define a contextual ontology as an explicit specification of a conceptualization, while Barkat [18] proposes a complete and comprehensive methodology to design multi-contextual semantic data warehouses. This contribution is aimed to provide a context meta model (language) that unifies the definitions provided in Database literature.…”

Section: Related Workmentioning

confidence: 99%

A Report-Driven Approach to Design Multidimensional Models

Azzini¹,

Marrara²,

Maurino

et al. 2019

Lecture Notes in Business Information Processing

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Today, large organisations and regulated markets are subject to the control of external audit associations, which require the submission of a huge amount of information in the form of predefined and rigidly structured reports. The compilation of these reports requires the extraction, transformation and integration of data from different heterogeneous operational databases. This task is usually performed by developing a software ad hoc for each report, or by adopting a data warehouse and analysis tools, which are now established technologies. Unfortunately, the data warehousing process is notoriously long and error prone, and is therefore particularly inefficient when the output of the data warehousing is represented by a limited number of reports. This article presents "MMBR", an approach that can generate a multidimensional model from the structure of expected reports as data warehouse output. The approach is able to generate the multidimensional model and populate the data warehouse by defining a knowledge base specific to the domain. Although the use of semantic information in data storage is not new, the novel contribution of our approach is represented by the idea of simplifying the design phase of the data warehouse, making it more efficient, by using an industry-specific knowledge base and a report-based approach.

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“…The author in [37] proposes a rewriting-queries algorithm that makes use of contextual hierarchies available in a data warehouse. The author in [38] puts forward a comprehensive contextualized DW design approach by integrating a generic context model that take in consideration concepts as well as properties.…”

Section: Data Warehouse and Contextmentioning

confidence: 99%

Linking Context to Data Warehouse Design

Aadil¹,

Kzaz²,

Wakrime³

et al. 2019

ijacsa

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Data warehouses are now widely used for analysis and decision support purposes. The availability of software solutions, which are more and more user-friendly and easy to manipulate has made it possible to extend their use to end users who are not specialists in the field of business intelligence. The purpose of this article is to provide an approach that assists nonexpert users in the data warehouse design process and integrates their contextual data. As well as to provide a method that assists non-expert users in data warehouse design process while incorporating their contextual data. Our proposal consists of a context model and a comprehensive Data Warehouse construction method that attaches the context to data warehouses and uses it to produce customized data marts adapted to the decision makers context.

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Bridging context and data warehouses through ontologies

Cited by 5 publications

References 11 publications

Using Adaptive Logics for Expression of Context and Interoperability in DL Ontologies

Using Adaptive Logics for Expression of Context and Interoperability in DL Ontologies

A Report-Driven Approach to Design Multidimensional Models

Linking Context to Data Warehouse Design

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