2015
Interoperability and system integration are central problems that limit the effective use of health information systems to improve efficiency and effectiveness of health service delivery. There is currently no proven technology that provides a general solution in low and middle income countries where the challenges are especially acute. Engineering health information systems in low resource environments have several challenges that include poor infrastructure, skills shortages, fragmented and piecemeal applications deployed and managed by multiple organisations as well as low levels of resourcing. An important element of modern solutions to these problems is a health information exchange that enable disparate systems to share health information. It is a challenging task to develop systems as complex as health information exchanges that will have wide applicability in low and middle income countries. This work takes a case study approach and uses the development of a health information exchange in Rwanda as the case study. This research reports on the design, implementation and analysis of an architecture, the Health Information Mediator, that is a central component of a health information exchange. While such architectures have been used successfully in high income countries their efficacy has not been demonstrated in low and middle income countries. The Rwandan case study was used to understand and identify the challenges and requirements for health information exchange in low and middle income countries. These requirements were used to derive a set of key concerns for the architecture that were then used to drive its design. Novel features of the architecture include: the ability to mediate messages at both the service provider and service consumer interfaces; support for multiple internal representations of messages to facilitate the adoption of new and evolving standards; and the provision of a general method for mediating health information exchange transactions agnostic of the type of transactions. The architecture is shown to satisfy the key concerns and was validated by implementing and deploying a reference application, the OpenHIM, within the Rwandan health information exchange. The architecture is also analysed using the Architecture Trade-off Analysis Method. It has also been successfully implemented in other low and middle income countries with relatively minor configuration changes which demonstrates the architectures generalizability.
@phdthesis{110,
author = {Ryan Crichton and Anban Pillay and Deshen Moodley},
title = {The Open Health Information Mediator: an Architecture for Enabling Interoperability in Low to Middle Income Countries},
abstract = {Interoperability and system integration are central problems that limit the effective use of health information systems to improve efficiency and effectiveness of health service delivery. There is currently no proven technology that provides a general solution in low and middle income countries where the challenges are especially acute. Engineering health information systems in low resource environments have several challenges that include poor infrastructure, skills shortages, fragmented and piecemeal applications deployed and managed by multiple organisations as well as low levels of resourcing. An important element of modern solutions to these problems is a health information exchange that enable disparate systems to share health information.
It is a challenging task to develop systems as complex as health information exchanges that will have wide applicability in low and middle income countries. This work takes a case study approach and uses the development of a health information exchange in Rwanda as the case study. This research reports on the design, implementation and analysis of an architecture, the Health Information Mediator, that is a central component of a health information exchange. While such architectures have been used successfully in high income countries their efficacy has not been demonstrated in low and middle income countries. The Rwandan case study was used to understand and identify the challenges and requirements for health information exchange in low and middle income countries. These requirements were used to derive a set of key concerns for the architecture that were then used to drive its design. Novel features of the architecture include: the ability to mediate messages at both the service provider and service consumer interfaces; support for multiple internal representations of messages to facilitate the adoption of new and evolving standards; and the provision of a general method for mediating health information exchange transactions agnostic of the type of transactions.
The architecture is shown to satisfy the key concerns and was validated by implementing and deploying a reference application, the OpenHIM, within the Rwandan health information exchange. The architecture is also analysed using the Architecture Trade-off Analysis Method. It has also been successfully implemented in other low and middle income countries with relatively minor configuration changes which demonstrates the architectures generalizability.},
year = {2015},
volume = {MSc},
}
2014
Poor adherence to prescribed treatment is a major factor contributing to tuberculosis patients developing drug resistance and failing treatment. Treatment adherence behaviour is influenced by diverse personal, cultural and socio-economic factors that vary between regions and communities. Decision network models can potentially be used to predict treatment adherence behaviour. However, determining the network structure (identifying the factors and their causal relations) and the conditional probabilities is a challenging task. To resolve the former we developed an ontology supported by current scientific literature to categorise and clarify the similarity and granularity of factors
@{158,
author = {Olukunle Ogundele and Deshen Moodley and Chris Seebregts and Anban Pillay},
title = {Building Semantic Causal Models to Predict Treatment Adherence for Tuberculosis Patients in Sub-Saharan Africa},
abstract = {Poor adherence to prescribed treatment is a major factor contributing to tuberculosis patients developing drug resistance and failing treatment. Treatment adherence behaviour is influenced by diverse personal, cultural and socio-economic factors that vary between regions and communities. Decision network models can potentially be used to predict treatment adherence behaviour. However, determining the network structure (identifying the factors and their causal relations) and the conditional probabilities is a challenging task. To resolve the former we developed an ontology supported by current scientific literature to categorise and clarify the similarity and granularity of factors},
year = {2014},
journal = {4th International Symposium (FHIES 2014) and 6th International Workshop (SEHC 2014)},
pages = {81-95},
month = {17/07-18/07},
}
One of the challenges in the Software Development Life Cycle (SDLC) is to ensure that the requirements that drive the development of a software system are correct. However, establishing unambiguous and error-free requirements is not a trivial problem. As part of the requirements phase of the SDLC, a conceptual model can be created which describes the objects, relationships and operations that are of importance to business. Such a conceptual model is often expressed as a UML class diagram. Recent research concerned with the formal validation of such UML class diagrams has focused on transforming UML class diagrams to various formalisms such as description logics. Description logics are desirable since they have reasoning support which can be used to show that a UML class diagram is consistent/inconsistent. Yet, even when a UML class diagram is consistent, it still does not address the problem of ensuring that a UML class diagram represents business requirements accurately. To validate such diagrams business analysts use a technique called scenario testing. In this paper we present an approach for the formal validation of UML class diagrams based on scenario testing. We additionally provide preliminary feedback on the experiences gained from using our scenario testing approach on a real-world software project.
@misc{106,
author = {Henriette Harmse and Katarina Britz and Aurona Gerber and Deshen Moodley},
title = {Scenario Testing using Formal Ontologies},
abstract = {One of the challenges in the Software Development Life Cycle (SDLC) is to ensure that the requirements that drive the development of a software system are correct. However, establishing unambiguous and error-free requirements is not a trivial problem. As part of the requirements phase of the SDLC, a conceptual model can be created which describes the objects, relationships and operations that are of importance to business. Such a conceptual model is often expressed as a UML class diagram. Recent research concerned with the formal validation of such UML class diagrams has focused on transforming UML class diagrams to various formalisms such as description logics. Description logics are desirable since they have reasoning support which can be used to show that a UML class diagram is consistent/inconsistent. Yet, even when a UML class diagram is consistent, it still does not address the problem of ensuring that a UML class diagram represents business requirements accurately. To validate such diagrams business analysts use a technique called scenario testing. In this paper we present an approach for the formal validation of UML class diagrams based on scenario testing. We additionally provide preliminary feedback on the experiences gained from using our scenario testing approach on a real-world software project.},
year = {2014},
isbn = {urn:nbn:de:0074-1301-3},
url = {http://ceur-ws.org/Vol-1301/ontocomodise2014_10.pdf},
}
The development of drug resistance is a major factor imped- ing the efficacy of antiretroviral treatment of South Africa’s HIV infected population. While genotype resistance testing is the standard method to determine resistance, access to these tests is limited in low-resource set- tings. In this paper we investigate machine learning techniques for drug resistance prediction from routine treatment and laboratory data to help clinicians select patients for confirmatory genotype testing. The tech- niques, including binary relevance, HOMER, MLkNN, predictive clus- tering trees (PCT), RAkEL and ensemble of classifier chains were tested on a dataset of 252 medical records of patients enrolled in an HIV treat- ment failure clinic in rural KwaZulu-Natal in South Africa. The PCT method performed best with a discriminant power of 1.56 for two drugs, above 1.0 for three others and a mean true positive rate of 0.68. These methods show potential for application where access to genotyping is limited.
@{97,
author = {Pascal Brandt and Deshen Moodley and Anban Pillay and Chris Seebregts and T. de Oliveira},
title = {An Investigation of Classification Algorithms for Predicting HIV Drug Resistance Without Genotype Resistance Testing},
abstract = {The development of drug resistance is a major factor imped- ing the efficacy of antiretroviral treatment of South Africa’s HIV infected population. While genotype resistance testing is the standard method to determine resistance, access to these tests is limited in low-resource set- tings. In this paper we investigate machine learning techniques for drug resistance prediction from routine treatment and laboratory data to help clinicians select patients for confirmatory genotype testing. The tech- niques, including binary relevance, HOMER, MLkNN, predictive clus- tering trees (PCT), RAkEL and ensemble of classifier chains were tested on a dataset of 252 medical records of patients enrolled in an HIV treat- ment failure clinic in rural KwaZulu-Natal in South Africa. The PCT method performed best with a discriminant power of 1.56 for two drugs, above 1.0 for three others and a mean true positive rate of 0.68. These methods show potential for application where access to genotyping is limited.},
year = {2014},
journal = {Third International Symposium on Foundations of Health Information Engineering and Systems},
pages = {236-253},
month = {21/08-23/08},
isbn = {978-3-642-53955-8},
url = {http://link.springer.com/chapter/10.1007/978-3-642-53956-5_16},
}
The sugarcane supply chain (from sugarcane grower to mill) have particular challenges. One of these is that the growers have to deliver their cane to the mill before its quality degrades. The sugarcane supply chain typically consists of many growers and a mill. Growers deliver their cane daily during the milling season; the amount of cane they deliver depends on their farm size. Growers make decisions about when to harvest the cane, and the number and type of trucks needed to deliver their cane. The mill wants a consistent cane supply over the milling season. Growers are sometimes affected long queue lengths at the mill when they offload their cane. A preliminary agent-based simulation model was developed to understand this complex system. The model inputs a number of growers, and the amount of cane they are to deliver over the milling season. The number of trucks needed by each grower is determined by the trip, loading and unloading times and the anticipated waiting time at the mill. The anticipated waiting time was varied to determine how many trucks would be needed in the system to deliver the week’s cane allocation. As the anticipated waiting time increased, the number of trucks needed also increased, which in turn delayed the trucks when queuing at the mill. The growers’ anticipated waiting times never matched the actual waiting times. The research shows the promise of agent-based models as a sense-making approach to understanding systems where there are many individuals who have autonomous behaviour, and whose actions and interactions can result in unexpected system-level behaviour.
@{94,
author = {C. Sue Price and Deshen Moodley and C.N. Bezuidenhout},
title = {Using agent-based simulation to explore sugarcane supply chain transport complexities at a mill scale},
abstract = {The sugarcane supply chain (from sugarcane grower to mill) have particular challenges. One of these is that the growers have to deliver their cane to the mill before its quality degrades. The sugarcane supply chain typically consists of many growers and a mill. Growers deliver their cane daily during the milling season; the amount of cane they deliver depends on their farm size. Growers make decisions about when to harvest the cane, and the number and type of trucks needed to deliver their cane. The mill wants a consistent cane supply over the milling season. Growers are sometimes affected long queue lengths at the mill when they offload their cane.
A preliminary agent-based simulation model was developed to understand this complex system. The model inputs a number of growers, and the amount of cane they are to deliver over the milling season. The number of trucks needed by each grower is determined by the trip, loading and unloading times and the anticipated waiting time at the mill. The anticipated waiting time was varied to determine how many trucks would be needed in the system to deliver the week’s cane allocation. As the anticipated waiting time increased, the number of trucks needed also increased, which in turn delayed the trucks when queuing at the mill. The growers’ anticipated waiting times never matched the actual waiting times. The research shows the promise of agent-based models as a sense-making approach to understanding systems where there are many individuals who have autonomous behaviour, and whose actions and interactions can result in unexpected system-level behaviour.},
year = {2014},
journal = {43rd Annual Operations Research Society of South Africa Conference},
pages = {88-96},
month = {14/09-17/09},
isbn = {978-1-86822-656-6},
}
South Africa has one of the highest HIV infection rates in the world with more than 5.6 million infected people and consequently has the largest antiretroviral treatment program with more than 1.5 million people on treatment. The development of drug resistance is a major factor impeding the efficacy of antiretroviral treatment. While genotype resistance testing (GRT) is the standard method to determine resistance, access to these tests is limited in resource-limited settings. This research investigates the efficacy of multi-label machine learning techniques at predicting HIV drug resistance from routine treatment and laboratory data. Six techniques, namely, binary relevance, HOMER, MLkNN, predictive clustering trees (PCT), RAkEL and ensemble of classifier chains (ECC) have been tested and evaluated on data from medical records of patients enrolled in an HIV treatment failure clinic in rural KwaZulu-Natal in South Africa. The performance is measured using five scalar evaluation measures and receiver operating characteristic (ROC) curves. The techniques were found to provide useful predictive information in most cases. The PCT and ECC techniques perform best and have true positive prediction rates of 97% and 98% respectively for specific drugs. The ECC method also achieved an AUC value of 0.83, which is comparable to the current state of the art. All models have been validated using 10 fold cross validation and show increased performance when additional data is added. In order to make use of these techniques in the field, a tool is presented that may, with small modifications, be integrated into public HIV treatment programs in South Africa and could assist clinicians to identify patients with a high probability of drug resistance.
@phdthesis{93,
author = {Pascal Brandt and Deshen Moodley and Anban Pillay},
title = {An Investigation Of Multi-label Classification Techniques For Predicting Hiv Drug Resistance In Resource-limited Settings},
abstract = {South Africa has one of the highest HIV infection rates in the world with more than 5.6 million infected people and consequently has the largest antiretroviral treatment program with more than 1.5 million people on treatment. The development of drug resistance is a major factor impeding the efficacy of antiretroviral treatment. While genotype resistance testing (GRT) is the standard method to determine resistance, access to these tests is limited in resource-limited settings. This research investigates the efficacy of multi-label machine learning techniques at predicting HIV drug resistance from routine treatment and laboratory data. Six techniques, namely, binary relevance, HOMER, MLkNN, predictive clustering trees (PCT), RAkEL and ensemble of classifier chains (ECC) have been tested and evaluated on data from medical records of patients enrolled in an HIV treatment failure clinic in rural KwaZulu-Natal in South Africa. The performance is measured using five scalar evaluation measures and receiver operating characteristic (ROC) curves. The techniques were found to provide useful predictive information in most cases. The PCT and ECC techniques perform best and have true positive prediction rates of 97% and 98% respectively for specific drugs. The ECC method also achieved an AUC value of 0.83, which is comparable to the current state of the art. All models have been validated using 10 fold cross validation and show increased performance when additional data is added. In order to make use of these techniques in the field, a tool is presented that may, with small modifications, be integrated into public HIV treatment programs in South Africa and could assist clinicians to identify patients with a high probability of drug resistance.},
year = {2014},
volume = {MSc},
}
eHealth governance and regulation are necessary in low resource African countries to ensure effective and equitable use of health information technology and to realize national eHealth goals such as interoperability, adoption of standards and data integration. eHealth regulatory frameworks are under-developed in low resource settings, which hampers the progression towards coherent and effective national health information systems. Ontologies have the potential to clarify issues around interoperability and the effectiveness of different standards to deal with different aspects of interoperability. Ontologies can facilitate drafting, reusing, implementing and compliance testing of eHealth regulations. In this regard, we have developed an OWL ontology to capture key concepts and relations concerning interoperability and standards. The ontology includes an operational definition for interoperability and is an initial step towards the development of a knowledge representation modeling platform for eHealth regulation and governance.
@{92,
author = {Deshen Moodley and Chris Seebregts and Anban Pillay and Tommie Meyer},
title = {An Ontology for Regulating eHealth Interoperability in Developing African Countries},
abstract = {eHealth governance and regulation are necessary in low resource African countries to ensure effective and equitable use of health information technology and to realize national eHealth goals such as interoperability, adoption of standards and data integration. eHealth regulatory frameworks are under-developed in low resource settings, which hampers the progression towards coherent and effective national health information systems. Ontologies have the potential to clarify issues around interoperability and the effectiveness of different standards to deal with different aspects of interoperability. Ontologies can facilitate drafting, reusing, implementing and compliance testing of eHealth regulations. In this regard, we have developed an OWL ontology to capture key concepts and relations concerning interoperability and standards. The ontology includes an operational definition for interoperability and is an initial step towards the development of a knowledge representation modeling platform for eHealth regulation and governance.},
year = {2014},
journal = {Foundations of Health Information Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7789},
pages = {107-124},
month = {15/09},
isbn = {978-3-642-53955-8},
}
We modeled expert knowledge of arthropod flower-visiting behavioral ecology and represented this in an event-centric domain ontology, which we describe along with the ontology construction process. Two smaller domain ontologies were created to represent expert knowledge of known flower-visiting insect groups and expert knowledge of the flower-visiting behavioral ecology of Rediviva bees. Two application ontologies were designed, which, together with the domain ontologies, constituted the ontology framework of a prototype semantic enrichment and mediation system that we designed and implemented to improve semantic interoperability between flower-visiting data-stores. We describe and evaluate the system implementation in a case-study of three flower-visiting data-stores, and we discuss the system’s scalability, extension and potential impact. We demonstrate how the system is able to dynamically extract complex ecological interactions from heterogeneous specimen data-stores. The conceptual stance and modeling approach are potentially of general use in representing knowledge of animal behavior and ecological interactions, and in engineering semantic interoperability between data-stores containing behavioral ecology data.
@article{81,
author = {Willem Coetzer and Deshen Moodley and Aurona Gerber},
title = {A knowledge-based system for discovering ecological interactions in biodiversity data-stores of heterogeneous specimen-records: A case-study of flower-visiting ecology},
abstract = {We modeled expert knowledge of arthropod flower-visiting behavioral ecology and represented this in an event-centric domain ontology, which we describe along with the ontology construction process. Two smaller domain ontologies were created to represent expert knowledge of known flower-visiting insect groups and expert knowledge of the flower-visiting behavioral ecology of Rediviva bees. Two application ontologies were designed, which, together with the domain ontologies, constituted the ontology framework of a prototype semantic enrichment and mediation system that we designed and implemented to improve semantic interoperability between flower-visiting data-stores. We describe and evaluate the system implementation in a case-study of three flower-visiting data-stores, and we discuss the system’s scalability, extension and potential impact. We demonstrate how the system is able to dynamically extract complex ecological interactions from heterogeneous specimen data-stores. The conceptual stance and modeling approach are potentially of general use in representing knowledge of animal behavior and ecological interactions, and in engineering semantic interoperability between data-stores containing behavioral ecology data.},
year = {2014},
journal = {Ecological Informatics},
publisher = {Elsevier},
}
2013
No Abstract
@misc{68,
author = {Willem Coetzer and Deshen Moodley and Aurona Gerber},
title = {Implementing a semantic mediator to integrate flower-visiting records from South African natural history museums},
abstract = {No Abstract},
year = {2013},
}
Consolidating currently fragmented health information systems in low and middle-income countries (LMIC) into a coherent national information system will increase operational efficiencies, improve decision-making and will lead to better health outcomes. However, engineering an enterprise information system of the scale and complexity of a national health information system (NHIS) pose unique and complex challenges in LMICs. In this paper, we review current approaches to NHIS development and discuss challenges faced by LMICs to develop their NHIS. Based on current LMIC systems we identify three stages of system evolution and propose that LMICs should follow an evolutionary, middle-out approach to NHIS development supported by appropriate architectural frameworks.
@{63,
author = {Thinasagree Mudaly and Deshen Moodley and Anban Pillay and Chris Seebregts},
title = {Architectural Frameworks for Developing National Health Information Systems in Low and Middle Income Countries},
abstract = {Consolidating currently fragmented health information systems in low and middle-income countries (LMIC) into a coherent national information system will increase operational efficiencies, improve decision-making and will lead to better health outcomes. However, engineering an enterprise information system of the scale and complexity of a national health information system (NHIS) pose unique and complex challenges in LMICs. In this paper, we review current approaches to NHIS development and discuss challenges faced by LMICs to develop their NHIS. Based on current LMIC systems we identify three stages of system evolution and propose that LMICs should follow an evolutionary, middle-out approach to NHIS development supported by appropriate architectural frameworks.},
year = {2013},
journal = {Proceedings of the First IEEE International Conference on Enterprise Systems (ES 2013), Cape Town, South Africa},
month = {07/11 - 08/11},
}
No Abstract
@{62,
author = {Willem Coetzer and Deshen Moodley and Aurona Gerber},
title = {A Case-Study of Ontology-Driven Semantic Mediation of Flower-Visiting Data from Heterogeneous Data-Stores in Three South African Natural History Collections},
abstract = {No Abstract},
year = {2013},
journal = {The Semantic Web: ESWC 2013 Satellite Events},
pages = {87-100},
month = {05/27},
address = {Berlin},
}
2012
Most African countries have limited health information systems infrastructure. Some health information system components are implemented but often on an adhoc, piecemeal basis, by foreign software developers and designed to solve specific problems. Little attention is usually paid to how these components can fit into an integrated national health information system and interoperate with other components. The Health Enterprise Architecture Laboratory was recently established in the School of Computer Science at the University of KwaZulu-Natal in South Africa to undertake research and build capacity in open health architectures for developing African countries. Based on field experiences and requirements in South Africa, Mozambique and Rwanda, the laboratory is evolving a generic Health Enterprise Architecture Framework and Repository of Tools specifically for low resource settings. In this paper we describe these three initiatives and the expected impact on implementing health information systems in developing African countries.
@inbook{16,
author = {Deshen Moodley and Anban Pillay and Chris Seebregts},
title = {Position Paper: Researching and Developing Open Architectures for National Health Information Systems in Developing African Countries},
abstract = {Most African countries have limited health information systems infrastructure. Some health information system components are implemented but often on an adhoc, piecemeal basis, by foreign software developers and designed to solve specific problems. Little attention is usually paid to how these components can fit into an integrated national health information system and interoperate with other components. The Health Enterprise Architecture Laboratory was recently established in the School of Computer Science at the University of KwaZulu-Natal in South Africa to undertake research and build capacity in open health architectures for developing African countries. Based on field experiences and requirements in South Africa, Mozambique and Rwanda, the laboratory is evolving a generic Health Enterprise Architecture Framework and Repository of Tools specifically for low resource settings. In this paper we describe these three initiatives and the expected impact on implementing health information systems in developing African countries.},
year = {2012},
journal = {Foundations of Health Informatics Engineering and Systems, Revised and Selected Papers, Lecture Notes in Computer Science Volume 7151},
pages = {129-139},
publisher = {Springer},
url = {http://link.springer.com/chapter/10.1007/978-3-642-32355-3_8},
}
Rwanda, one of the smallest and most densely populated countries in Africa, has made rapid and substantial progress towards designing and deploying a national health information system. One of the challenging aspects of the system is the design of an architecture to support: interoperability between existing health information systems already in use in the country; incremental extension into a full integrated national health information system without substantial reengineering;and scaling, from a single district in the initial phase, to national level without requiring a fundamental change in technology or design paradigm. This paper describes the key requirements and the design of the current architecture using ISO/IEC/IEEE 42010 standard architecture descriptions. The architecture is based on the Enterprise Service Bus architectural model. We also describe a partial implementation of the architecture, and give a preliminary analysis based on our experiences.
@{10,
author = {Ryan Crichton and Deshen Moodley and Anban Pillay and R. Gakuba and Chris Seebregts},
title = {An Interoperability Architecture for the Health Information Exchange in Rwanda},
abstract = {Rwanda, one of the smallest and most densely populated countries in Africa, has made rapid and substantial progress towards designing and deploying a national health information system. One of the challenging aspects of the system is the design of an architecture to support: interoperability between existing health information systems already in use in the country; incremental extension into a full integrated national health information system without substantial reengineering;and scaling, from a single district in the initial phase, to national level without requiring a fundamental change in technology or design paradigm. This paper describes the key requirements and the design of the current architecture using ISO/IEC/IEEE 42010 standard architecture descriptions. The architecture is based on the Enterprise Service Bus architectural model. We also describe a partial implementation of the architecture, and give a preliminary analysis based on our experiences.},
year = {2012},
}
Sensor Web researchers are currently investigating middleware to aid in the dynamic discovery, integration and analysis of vast quantities of both high and low quality, but distributed and heterogeneous earth observation data. Key challenges being investigated include dynamic data integration and analysis, service discovery and semantic interoperability. However, few efforts deal with managing knowledge and system dynamism. Two emerging technologies that have shown promise in dealing with these issues are ontologies and software agents. This paper presents an integrated ontology driven agent based Sensor Web architecture for managing knowledge and system dynamism. An application case study on wildfire detection is used to illustrate the operation of the architecture.
@article{8,
author = {Deshen Moodley and I. Simonis and J. Tapamo},
title = {An architecture for managing knowledge and system dynamism in the worldwide Sensor Web},
abstract = {Sensor Web researchers are currently investigating middleware to aid in the dynamic discovery, integration and analysis of vast quantities of both high and low quality, but distributed and heterogeneous earth observation data. Key challenges being investigated include dynamic data integration and analysis, service discovery and semantic interoperability. However, few efforts deal with managing knowledge and system dynamism. Two emerging technologies that have shown promise in dealing with these issues are ontologies and software agents. This paper presents an integrated ontology driven agent based Sensor Web architecture for managing knowledge and system dynamism. An application case study on wildfire detection is used to illustrate the operation of the architecture.},
year = {2012},
journal = {International Journal of Semantic Web and Information Systems: Special issue on Semantics-enhanced Sensor Networks, Internet of Things and Smart Devices},
volume = {8},
pages = {64-88},
issue = {1},
url = {http://www.igi-global.com/article/architecture-managing-knowledge-system-dynamism/70587},
}
2011
No Abstract
@{9,
author = {Deshen Moodley and J. Tapamo},
title = {A semantic infrastructure for a Knowledge Driven Sensor Web},
abstract = {No Abstract},
year = {2011},
journal = {Proceedings of the 4th International Workshop on Semantic Sensor Networks 2011 (SSN11), 23 October 2011,Bonn, Germany, A workshop of the 10th International Semantic Web Conference (ISWC 2011)},
}
