The Collaborative Business Intelligence Ontology (CBIOnt)
Muhammad Fahad (ERIC), J\'er\^ome Darmont (ERIC), C\'ecile Favre, (ERIC)

TL;DR
The paper introduces CBIOnt, an OWL 2 DL ontology designed to model and infer information about collaborative business intelligence sessions, capturing content, context, and spatial-temporal data for improved semantic understanding.
Contribution
It presents a novel ontology framework, CBIOnt, that formalizes collaborative BI sessions, integrating content and contextual information for semantic Web applications.
Findings
CBIOnt effectively models collaborative sessions with content and context.
Enables inference of session-related information on semantic Web.
Supports diverse collaborative scenarios in business intelligence.
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…
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Taxonomy
TopicsSemantic Web and Ontologies · Big Data and Business Intelligence · Business Process Modeling and Analysis
