A rule-based ontology reasoning for scientific effects retrieval

Ma, Jun; Zhang, Quan; Zhang, Jinling; Zhang, Jianhui

doi:10.1109/icmit.2012.6225810

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…SO are represented as explicit forms of shared conceptualisations in a given domain that are able to create different forms of relationships and model pieces of concepts that ends up representing the reasoning about a given body of knowledge. According to research by Ma et al, [10] ontologies are able to be used for different projects when designing products, this can only be achieved based on how information of a given product might be disseminated in different domains. Based on this premise, SO is used as a way of representing the domain conceptualisations that is needed by the product if the data semantics have to be captured.…”

Section: Scientific Ontologiesmentioning

confidence: 99%

Onto-Engineering: A Conceptual framework for Integrating Requirement Engineering Process with scientifically tuned Digital Forensics Ontologies

Kebande¹,

Maake²

2017

IJCSDF

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A framework for integrating Requirement Engineering (RE) with scientifically tuned Digital Forensics Ontologies (SDFO) envisages a semantic web-driven approach that is able to provide a shared understanding of unifying RE techniques coupled with digital investigation techniques that are tuned from an ontological perspective. In the context of this paper, RE has been portrayed as a discipline that can not only be able to validate, specify, analyse and provide elicitation of the requirements but also to manage them effectively. Nevertheless, SDFO have been employed as bodies of knowledge that provides a shared understanding of knowledge or discipline within the Digital Forensic (DF) domain that helps to solve some given problems. Mainly, this requires the mapping/integrating of RE processes to DF tuned ontologies. The objective of the work presented in this paper, therefore, is to show how RE can be integrated into SDFO with the aim of identifying the most effective scientific approaches using an OntoTuning Matcher (OTM) that has been proposed in this paper. This paper was able to represent a scientifically tuned approach using the Automatic Semantic Mapping of Ontologies (ASMOV) approach. ASMOV provides an approach that is able to align ontologies with other systems such that inconsistencies are eliminated and the accuracy is increased. The contribution of the paper is presented in two folds: Firstly, the author identifies a high-level Onto-Engineered framework for integrating RE and SDFO, thereafter, a more detailed Onto-Engineered framework is discussed. The Onto-Engineered framework that has been discussed in this paper will help to clarify different diversification aspects that exists between RE and SDFO.

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Section: Scientific Ontologiesmentioning

confidence: 99%