OntoRT: An Ontology Model for Role-Based Trust-Management Framework

2011 ◽  
Vol 58-60 ◽  
pp. 2085-2090 ◽  
Author(s):  
Xin Xin Liu ◽  
Shao Hua Tang ◽  
Kai Wei
Keyword(s):  
Trust Management ◽  
Domain Knowledge ◽  
Description Logic ◽  
Collaborative Systems ◽  
Large Fragment ◽  
Management Framework ◽  
Rich Domain ◽  
Ontology Model ◽  
Logical Formalization ◽  
Role Based

This paper presents OntoRT, an ontology model for Role-base Trust-management(RT) framework, which covers a large fragment of RT including RT0, RT1, RT2 and application domain specification documents (ADSDs). RT addresses distributed authorization problems in decentralized collaborative systems. OntoRT establishes a common vocabulary for RT roles and policies across domains. We describe OntoRT formally in Description Logic(DL) SHOIN(D) and DL-safe SWRL rules. Basing on our logical formalization it is feasible to authorize and analyze RT policies automatically via the state of arts DL reasoners. Finally, we show how OntoRT can be integrated with OWL-DL ontologies which are W3C standard for representing information on the Web. By referring to OWL-DL ontologies that provide rich domain knowledge, specification and management of RT policies are simplified.

scholarly journals Capability-oriented architectural analysis method based on fuzzy description logic

2016 ◽  
Vol 13 (1) ◽  
pp. 287-308 ◽  
Author(s):  
Zhang Tingting ◽  
Liu Xiaoming ◽  
Wang Zhixue ◽  
Dong Qingchao
Keyword(s):  
Business Strategy ◽  
Domain Knowledge ◽  
Description Logic ◽  
Description Logics ◽  
Model Verification ◽  
Architectural Analysis ◽  
Requirements Modeling ◽  
Strategy Model ◽  
Domain Specific Modeling ◽  
Fuzzy Description

A number of problems may arise from architectural requirements modeling, including alignment of it with business strategy, model integration and handling the uncertain and vague information. The paper introduces a method for modeling architectural requirements in a way of ontology-based and capability-oriented requirements elicitation. The requirements can be modeled within a three-layer framework. The Capability Meta-concept Framework is provided at the top level. The domain experts can capture the domain knowledge within the framework, forming the domain ontology at the second level. The domain concepts can be used for extending the UML to produce a domain-specific modeling language. A fuzzy UML is introduced to model the vague and uncertain features of the capability requirements. An algorithm is provided to transform the fuzzy UML models into the fuzzy Description Logics ontology for model verification. A case study is given to demonstrate the applicability of the method.

scholarly journals Towards a Blockchain-based Identity and Trust Management Framework for the IoV Ecosystem

2020 ◽  
Author(s):  
Anastasia Theodouli ◽  
Konstantinos Moschou ◽  
Konstantinos Votis ◽  
Dimitrios Tzovaras ◽  
Jan Lauinger ◽  
...  
Keyword(s):  
Trust Management ◽  
Management Framework

scholarly journals Data management for developing digital twin ontology model

2020 ◽  
pp. 095440542097811
Author(s):  
Sumit Singh ◽  
Essam Shehab ◽  
Nigel Higgins ◽  
Kevin Fowler ◽  
Dylan Reynolds ◽  
...  
Keyword(s):  
Data Management ◽  
Data Model ◽  
Domain Knowledge ◽  
Conceptual Knowledge ◽  
Current Approach ◽  
Model Structure ◽  
Digital Twin ◽  
Ontology Model ◽  
Minimum Data ◽  
Novel Concept

Digital Twin (DT) is the imitation of the real world product, process or system. Digital Twin is the ideal solution for data-driven optimisations in different phases of the product lifecycle. With the rapid growth in DT research, data management for digital twin is a challenging field for both industries and academia. The challenges for DT data management are analysed in this article are data variety, big data & data mining and DT dynamics. The current research proposes a novel concept of DT ontology model and methodology to address these data management challenges. The DT ontology model captures and models the conceptual knowledge of the DT domain. Using the proposed methodology, such domain knowledge is transformed into a minimum data model structure to map, query and manage databases for DT applications. The proposed research is further validated using a case study based on Condition-Based Monitoring (CBM) DT application. The query formulation around minimum data model structure further shows the effectiveness of the current approach by returning accurate results, along with maintaining semantics and conceptual relationships along DT lifecycle. The method not only provides flexibility to retain knowledge along DT lifecycle but also helps users and developers to design, maintain and query databases effectively for DT applications and systems of different scale and complexities.

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