author_facet Shaban-Nejad, Arash
Ormandjieva, Olga
Kassab, Mohamad
Haarslev, Volker
Shaban-Nejad, Arash
Ormandjieva, Olga
Kassab, Mohamad
Haarslev, Volker
author Shaban-Nejad, Arash
Ormandjieva, Olga
Kassab, Mohamad
Haarslev, Volker
spellingShingle Shaban-Nejad, Arash
Ormandjieva, Olga
Kassab, Mohamad
Haarslev, Volker
International Journal of Telemedicine and Applications
Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
Health Information Management
Computer Networks and Communications
Health Informatics
Medicine (miscellaneous)
author_sort shaban-nejad, arash
spelling Shaban-Nejad, Arash Ormandjieva, Olga Kassab, Mohamad Haarslev, Volker 1687-6415 1687-6423 Hindawi Limited Health Information Management Computer Networks and Communications Health Informatics Medicine (miscellaneous) http://dx.doi.org/10.1155/2009/917826 <jats:p>Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.</jats:p> Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory International Journal of Telemedicine and Applications
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title Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_unstemmed Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_full Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_fullStr Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_full_unstemmed Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_short Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_sort managing requirement volatility in an ontology-driven clinical lims using category theory
topic Health Information Management
Computer Networks and Communications
Health Informatics
Medicine (miscellaneous)
url http://dx.doi.org/10.1155/2009/917826
publishDate 2009
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description <jats:p>Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.</jats:p>
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author Shaban-Nejad, Arash, Ormandjieva, Olga, Kassab, Mohamad, Haarslev, Volker
author_facet Shaban-Nejad, Arash, Ormandjieva, Olga, Kassab, Mohamad, Haarslev, Volker, Shaban-Nejad, Arash, Ormandjieva, Olga, Kassab, Mohamad, Haarslev, Volker
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description <jats:p>Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.</jats:p>
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spelling Shaban-Nejad, Arash Ormandjieva, Olga Kassab, Mohamad Haarslev, Volker 1687-6415 1687-6423 Hindawi Limited Health Information Management Computer Networks and Communications Health Informatics Medicine (miscellaneous) http://dx.doi.org/10.1155/2009/917826 <jats:p>Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.</jats:p> Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory International Journal of Telemedicine and Applications
spellingShingle Shaban-Nejad, Arash, Ormandjieva, Olga, Kassab, Mohamad, Haarslev, Volker, International Journal of Telemedicine and Applications, Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory, Health Information Management, Computer Networks and Communications, Health Informatics, Medicine (miscellaneous)
title Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_full Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_fullStr Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_full_unstemmed Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_short Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
title_sort managing requirement volatility in an ontology-driven clinical lims using category theory
title_unstemmed Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory
topic Health Information Management, Computer Networks and Communications, Health Informatics, Medicine (miscellaneous)
url http://dx.doi.org/10.1155/2009/917826