Semantic Management of Nonfunctional Requirements in an e-Health System Nigel Koay, Pavandeep Kataria, and Radmilla Juric, Dipl.-Ing. University of Westminster, London, United Kingdom. 2010 Telemedicine and e-Health
Jan 03, 2016
Semantic Management of NonfunctionalRequirements in an e-Health System
Nigel Koay, Pavandeep Kataria, and Radmilla Juric, Dipl.-Ing.University of Westminster, London, United Kingdom.2010Telemedicine and e-Health
Introduction
Remote patient monitoring systemsTo give an objective measure of the patient’s status at any given timeTo interpret data generated by remote monitoring mechanisms to patients and healthcare professionalsTo assist patients in terms of informing, advising, alerting, and making decisions locallyTo assist the healthcare professional in their role as healthcare providers
Introduction
To give an objective measure of the patient’s status at any given time
monitor patients in terms of measuring a variety of conditions, experiences, feelings, disabilities, and situations specific for such patientsThe monitoring should be personalized for a particular patient and should include a set of devices that fit the personalized picture of patient’s needs
→which ones of the devices satisfy specific criteria for creating a particular RPMS
Methods
Methods
Semantic management means exploiting the semantics stored in the scenario
Ontological engineeringsemantic Web tools and languages
→ 4 Steps of process
Methods
Create ontological concepts based on the semantics from the scenario
Req-ONTO stores semantics related to a particular patient and the way he uses the RPMSDev-ONTO stores the semantic applicable to any device that may or may not be a part of the RPMS
Exploit the ontological models through domain and range constraints, OWL restrictions, and assertions to strengthen the relationships between semantics stored in both ontology
MethodsPerform the alignment process between Req-ONTO and Dev-ONTO to find matches between semantically related concepts of ontologies
The first match M1 is between User Preferences to Device ConstraintsThe second match M2 is between User Disability and Device Purpose
We manipulate the discoveries of these matches M1 and M2 through high-level reasoning into new ontological concepts that contain the answer to our question
Methods
MethodsReq-ontology
MethodsDev-ontology
Methods
Rule 1 makes a match between user’s preferences and a device that accommodates the preferencesRule 2 makes a match between a disability and a device that monitors the disability
Methods
Rule 3 runs on top of rules 1 and 2. It takes the results of both rules and incorporates additional preferences, specified by the user. The result will be a device deemed to be the best choice
DiscussionOur semantic modeling of the RPMS environment allows any classification from the Diagnosis-Related Group systems to become a part of Req-ONTOFurther, our proposal can be extended into any environment that depends on taking an ‘‘objective measure’’ of the patient’s status at any given timeIn other words, our idea is reusable in case management, where a particular patient’s ‘‘situation’’ determines what is to be measured
Conclusionwe explore ontologies and Web semantic tools when managing nonfunctional requirements in e-healthcareWe have created two ontologies: Req-ONTO and Dev-ONTO, which store semantics of nonfunctional requirements imposed on our RPMS and the characteristics of devicesour idea to use ontological environments in systemizing unstructured nonfunctional requirements proved to be a good starting point in building personalized pervasive e-health services