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Capturing the Context of Concepts using the Transaction Graph through a Mobile NHS Case Study

Capturing the Context of Concepts using the Transaction Graph through a Mobile NHS Case Study

Ivan Launders
Copyright: © 2016 |Volume: 4 |Issue: 1 |Pages: 13
ISSN: 2166-7292|EISSN: 2166-7306|EISBN13: 9781466693722|DOI: 10.4018/IJCSSA.2016010102
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MLA

Launders, Ivan. "Capturing the Context of Concepts using the Transaction Graph through a Mobile NHS Case Study." IJCSSA vol.4, no.1 2016: pp.35-47. http://doi.org/10.4018/IJCSSA.2016010102

APA

Launders, I. (2016). Capturing the Context of Concepts using the Transaction Graph through a Mobile NHS Case Study. International Journal of Conceptual Structures and Smart Applications (IJCSSA), 4(1), 35-47. http://doi.org/10.4018/IJCSSA.2016010102

Chicago

Launders, Ivan. "Capturing the Context of Concepts using the Transaction Graph through a Mobile NHS Case Study," International Journal of Conceptual Structures and Smart Applications (IJCSSA) 4, no.1: 35-47. http://doi.org/10.4018/IJCSSA.2016010102

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Abstract

This paper reports the use of Conceptual Graphs and Peirce Logic by enterprise architects, who need to capture conceptual context represented in business terms, which differ conceptually from the same terms used in the medical context. For example, in a UK Mobile NHS case study the medical context drug-drug refers to interactions in a health treatment regime of two or more drugs, where the effects of one drug on another can be increased or decreased, or can produce a new effect that neither produces alone. In a business context drug-drug refers to an economic event and resource impact alert in a patient record database that suggests a new or replacement drug that changes the cost of treatment. The paper explains how TrAM automation can capture typical (canonical) use, focused on economic events and associated resource impacts, and can provide exploration of the Resource, Events, and Agents of the Transaction Model through use of Transaction Graph ontology.

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