Semantic Management of Nonfunctional Requirements in an e-Health System

1. Semantic Management of NonfunctionalRequirements in an e-Health System Nigel Koay, PavandeepKataria,and RadmillaJuric, Dipl.-Ing. University of Westminster, London, United Kingdom. 2010 Telemedicine and e-Health

2. Introduction • Remote patient monitoring systems • To give an objective measure of the patient’s status at any given time • To interpret data generated by remote monitoring mechanisms to patients and healthcare professionals • To assist patients in terms of informing, advising, alerting, and making decisions locally • To assist the healthcare professional in their role as healthcare providers

3. 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 patients • The 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

4. Methods

5. Methods • Semantic management means exploiting the semantics stored in the scenario • Ontological engineering • semantic Web tools and languages • → 4 Steps of process

6. 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 RPMS • Dev-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

7. Methods • Perform 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 Constraints • The 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

8. Methods

9. MethodsReq-ontology

10. MethodsDev-ontology

11. Methods • Rule 1 makes a match between user’s preferences and a device that accommodates the preferences • Rule 2 makes a match between a disability and a device that monitors the disability

12. 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

13. Discussion • Our semantic modeling of the RPMS environment allows anyclassification from the Diagnosis-Related Group systems to become a part of Req-ONTO • Further, our proposal can be extended into any environment that depends on taking an ‘‘objective measure’’ of the patient’s status at any given time • In other words, our idea is reusable in case management, where a particular patient’s ‘‘situation’’ determines what is to be measured

14. Conclusion • we explore ontologies and Web semantic tools when managing nonfunctional requirements in e-healthcare • We have created two ontologies: Req-ONTO and Dev-ONTO, which store semantics of nonfunctional requirements imposed on our RPMS and the characteristics of devices • our idea to use ontological environments in systemizing unstructured nonfunctional requirements proved to be a good starting point in building personalized pervasive e-health services