Grant: Discovery Grants Program - Individual
University of Ontario Institute of Technology
$14,000.00
""Environment for Smart, Customizable, and Collaborative Service Analysis and Integration""
FY 2012-13
Summary
This research program provides models, techniques and tools for developing and analyzing collaborative, smart, and customizable service integration and decision making systems. It introduces ""consultant services"" as a new type of decision support systems that amalgamate semantic analysis techniques with the exploration nature of data mining operations to find an effective match between the user's desired features and the available web services, without overwhelming the user with long lists of possibilities, but only those with the highest semantic similarities. Furthermore, for sensitive application domains such as healthcare or banking, in-depth analysis of the distributed structural or behavioral properties of the candidate services may be necessary. This research provides two complementary techniques for in-depth service quality assessment. It provides dynamic analysis techniques based on execution pattern mining to explore the structural properties of distributed web services. It also provides a new technique based on test cases to assess the behavior aspects of candidate web services. This research proposes a new model for service infrastructure using a ""customizable expert agent"" which is inspired from real business enterprises. This new service is processed at the client's platform; hence it enhances the client's privacy and reduces network traffic. The customizable agent is used to implement the functionality of the proposed consultant services and service assessment techniques. The case-based and ad-hoc collaborative decision-making is increasingly important in health and medical environments. The collaborative teams require smart services to communicate and share information; access to patient's electronic health records and images; consult and make decisions; and diagnosis and treat patients. This program will provide the required infrastructure for a simulation environment, which will be compatible and interoperable with HL7 v3 messaging and SNOMED CT terminology system standards. Such an environment will also apply a new behavior-based access control mechanism to ensure data privacy in communicating and sharing sensitive information.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
293250-2012
Name nom
Sartipi, Kamran
Department département
Engineering and Applied Science, Faculty of
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2012
Award amount
14000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
800
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information and communication services
Area of application fr
Services d'information et de télécommunications
Research subject code
2706
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software engineering
Research subject fr
Génie logiciel
Partie
1
Nb partie
1
Application title
""Environment for Smart, Customizable, and Collaborative Service Analysis and Integration""
Keyword
NSERC
Application summary
This research program provides models, techniques and tools for developing and analyzing collaborative, smart, and customizable service integration and decision making systems. It introduces ""consultant services"" as a new type of decision support systems that amalgamate semantic analysis techniques with the exploration nature of data mining operations to find an effective match between the user's desired features and the available web services, without overwhelming the user with long lists of possibilities, but only those with the highest semantic similarities. Furthermore, for sensitive application domains such as healthcare or banking, in-depth analysis of the distributed structural or behavioral properties of the candidate services may be necessary. This research provides two complementary techniques for in-depth service quality assessment. It provides dynamic analysis techniques based on execution pattern mining to explore the structural properties of distributed web services. It also provides a new technique based on test cases to assess the behavior aspects of candidate web services. This research proposes a new model for service infrastructure using a ""customizable expert agent"" which is inspired from real business enterprises. This new service is processed at the client's platform; hence it enhances the client's privacy and reduces network traffic. The customizable agent is used to implement the functionality of the proposed consultant services and service assessment techniques. The case-based and ad-hoc collaborative decision-making is increasingly important in health and medical environments. The collaborative teams require smart services to communicate and share information; access to patient's electronic health records and images; consult and make decisions; and diagnosis and treat patients. This program will provide the required infrastructure for a simulation environment, which will be compatible and interoperable with HL7 v3 messaging and SNOMED CT terminology system standards. Such an environment will also apply a new behavior-based access control mechanism to ensure data privacy in communicating and sharing sensitive information.