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Conference Papers Year : 2022

The Collaborative Business Intelligence Ontology (CBIOnt)

Abstract

In the current era, many disciplines are seen devoted towards ontology development for their domains with the intention of creating, disseminating and managing resource descriptions of their domain knowledge into machine understandable and processable manner. Ontology construction is a difficult group activity that involves many people with the different expertise. Generally, domain experts are not familiar with the ontology implementation environments and implementation experts do not have all the domain knowledge. We have designed Collaborative Business Intelligence Ontology (CBIOnt) for BI4People project. In this paper, we present CBIOnt that is OWL 2 DL ontology for the description of collaborative session between different collaborators working together on the business intelligent platform. As the collaborative session between various collaborators belongs to some collaborative form, phase and research aspect, therefore CBIOnt captures this knowledge along with the collaborative session content (comments, questions, answers, etc.) so that one can inference various types of information stored on ontologies when required. In addition, it stores the location and temporal-spatial information about the collaboration held between collaborators. We believe CBIOnt serves as a formal framework for dealing with the collaborative session taken place among collaborators on the semantic Web.
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hal-03834085 , version 1 (28-10-2022)

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Muhammad Fahad, Jérôme Darmont, Cécile Favre. The Collaborative Business Intelligence Ontology (CBIOnt). 18e journées Business Intelligence et Big Data (EDA 2022), Oct 2022, Clermont-Ferrand, France. pp.61-72. ⟨hal-03834085⟩
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