Linking Context to Ontologies

Barkat, Okba; Bellatreche, Ladjel

doi:10.1109/skg.2015.36

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…CO are used for context design purposes in areas as diverse as e-commerce (Wang et al, 2012), databases (Barkat and Bellatreche, 2015), data engineering (Chen et al, 2005), etc. However, for the distinctive contexts associated with governmental processes, few works focuses on their use.…”

Section: Ontologies-based Approachesmentioning

confidence: 99%

A semantic approach for generating government processes

Cherouana¹,

Mahdaoui²,

Bellatreche³

et al. 2019

IJWGS

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In the last years, governments embraced business process management practices to improve their interactions and services with various stakeholders such as citizens, businesses and other government agencies. Nevertheless, current government process management solutions are still very limited at the semantic level, leading to challenges in dealing with legal, social, organisational, political and economic constraints, collectively referred to as 'context'. In this paper, we introduce a semantic government process management (SGPM) approach for the design and deployment of legally compliant government processes. The developed solution is mainly articulated around an ontological framework, with a high level of abstraction, allowing the explicit representation of legal context associated with government processes. It is connected to a defined legal meta-model that acts as legal context extraction guidelines and knowledge source. Moreover, this framework is substantiated by a legal features model allowing the semantic representation of structural relationships and dependencies between processes, sub-processes, as well as activities. The ontological framework is implemented as software assets, using OWL-DL, that constitute the kernel from which BPEL executable government processes are automatically generated.

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Section: Ontologies-based Approachesmentioning

confidence: 99%

A semantic approach for generating government processes

Cherouana¹,

Mahdaoui²,

Bellatreche³

et al. 2019

IJWGS

Self Cite

View full text Add to dashboard Cite

show abstract

“…More recently, (Barkat & Bellatreche, 2015) propose to model the context first, then link it toexistingdomainontologies.Inthiscase,thecontextbecomespartofthedatabaseaspartofan applicationandcanbequeriedasanentityofthedatabase.…”

Section: Ontology-based Context Modelingmentioning

confidence: 99%

Current Development of Ontology-Based Context Modeling

Zemmouchi-Ghomari

2018

International Journal of Distributed Artificial Intelligence

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Any information used to characterize the situation of an entity: a person, a place, or an object, can be considered as context. Indeed, context is crucial to avoid semantic ambiguity in data interpretation. However, linking data to its context is a recognized research issue. Adopting an ontology-based approach to model formally the context enables automatic interpretation and reasoning capabilities. This article discusses the main context modeling approaches based ontology by highlighting their principles, scenarios, use cases, benefits, and challenges to explore the use of ontologies to represent contexts.

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“…This is based on the domain ontology of the knowledge-based system and on a context ontology. Barkat et al [10] define a context ontology to integrate context into the semantic databases, called OntoDB. Hence, their approach is restricted to applications using exactly this database.…”

Section: Related Workmentioning

confidence: 99%

“…To address this issue, we provide an approach to automatically compose DIPs in a compact manner in order to relieve the decision maker from browsing complex IT systems and to redirect his focus on domain-specific problem-solving. We augment and go beyond existing approaches in providing relevant data via context-aware filtering [9], [10], [11] and data integration in engineering [6], [8] in order to fulfill domain-specific requirements. Key requirements are generation of DIPs without comprehensive IT knowledge; and integration of context-aware filtering into the existing engineering IT landscape.…”

Section: Introductionmentioning

confidence: 99%

Automated Creation and Provisioning of Decision Information Packages for the Smart Factory

Hoos

Hirmer

Mitschang

2018

J. Complex Syst. Inform. Model. Q.

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In recent years, Industry 4.0 emerges as a new trend, enabling the integration of data-intensive cyber physical systems, Internet of Things, and mobile applications, into production environments. Even though Industry 4.0 concentrates on automated engineering and manufacturing processing, the human actor is still important for decision making in the product lifecycle process. To support correct and efficient decision making, human actors have to be provided with relevant data depending on the current context. This data needs to be retrieved from distributed sources like bill of material systems, product data management and manufacturing execution systems, holding product model and factory model. In this article, we address this issue by introducing the concept of decision information packages, which enable to compose relevant engineering data for a specific context from distributed data sources. To determine relevant data, we specify a context-aware engineering data model and corresponding operators. To realize our approach, we provide an architecture and a prototypical implementation based on requirements of a real case scenario. This article is a revised and selected version of the previous work.

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Linking Context to Ontologies

Cited by 5 publications

References 15 publications

A semantic approach for generating government processes

A semantic approach for generating government processes

Current Development of Ontology-Based Context Modeling

Automated Creation and Provisioning of Decision Information Packages for the Smart Factory

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