Implementation of ontology for intelligent hospital ward

We have developed and implemented an ontology for an intelligent hospital ward. Our aim is to address the pervasiveness of computing applications in healthcare environments, which require: sharing of data across the hospital, including data generated by sensors and embedded in such environments, and dealing with semantic heterogeneity that exists across the hospital's data repositories. Our conceptual ontological model that supports such an environment has been implemented using semantic web tools and tested through the application developed with the J2EE technology

Multi-user investigation organizer

A system that allows a team of geographically dispersed users to collaboratively analyze a mishap event. The system includes a reconfigurable ontology, including instances that are related to and characterize the mishap, a semantic network that receives, indexes and stores, for retrieval, viewing and editing, the instances and links between the instances, a network browser interface for retrieving and viewing screens that present the instances and links to other instances and that allow editing thereof, and a rule-based inference engine, including a collection of rules associated with establishment of links between the instances. A possible conclusion arising from analysis of the mishap event may be characterized as one or more of: not a credible conclusion; an unlikely conclusion; a credible conclusion; conclusion needs analysis; conclusion needs supporting data; conclusion proposed to be closed; and an un-reviewed conclusion

A semantically-enriched quality governance framework in the system of systems context applied to cancer care

Organisations are becoming more complex with diverse businesses, and therefore accomplishing their business objectives entails the need to develop System of Systems (SoS) with new capabilities based on existing monolithic systems of different domains. Regardless of the business objectives of these organisations, they can only be achieved if the right level of quality is ensured across the SoS arrangement. In order to deliver new SoS capabilities, interoperability between the SoS’s Constituent Systems (CSs) is required. Semantic inconsistencies at different levels of SoS’s constituent systems causes various challenges which can degrade the level of quality governance among the SoS arrangement. These inconsistencies mainly are due to the domain process’ heterogeneities, multiple standards followed, policies and varying levels of quality requirements of the CSs, and hence the level of interoperability affecting the anticipated quality.To respond to the above challenges, this research is aimed at investigating the effectiveness of semantically-enriched quality governance in relation to policies, processes, standards and quality requirements of the constituent systems in a SoS arrangement. For this purpose, a semantically enriched framework for the quality governance of SoS, i.e. OntoSoS.QM.Gov (Ontology-based System of Systems Quality Management Governance) has been developed and evaluated incrementally using an adaptation of the Design Science Research Methodology (DSRM). A sufficient and representative case study has been utilised in the DSRM process increments from the SoS cancer care domain, in particular, the Cell Therapy and Applied Genomics (CTAG) at the King Hussein Cancer Centre (KHCC), Jordan. The OntoSoS.QM.Gov framework consists of four ontological models: (i) the SoS standards ontology model (OntoSoS.Stand), (ii) the SoS quality requirements ontology model (OntoSoS.QR), (iii) the SoS process ontology model (OntoSoS.Process), and (iv) the SoS policies ontology model (OntoSoS.Policy). They are linked together using a fit-for-purpose governance process in managing the semantics of the relevant quality governance areas.The outcomes of demonstrating the OntoSoS.QM.Gov framework using the CTAG case study and evaluating it with the cancer care domain experts revealed the following. First, semantic heterogeneities between CSs and SoS in relation to their policies, processes, quality requirements and standards have been resolved. Second, the fit- for- purpose quality governance process was observed to mostly determining and resolving conflicts with minimum human intervention. Third, the adequacy of the four ontological governance models in capturing the semantics of governance in relation to policies, processes, quality requirements and standards not only for CSs but also as stand-alone models that may further be utilised in different contexts or domains.Finally, this research has to identify further research areas to explore in relation to the governance of change management of constituent systems’ processes, policies, standards where their business processes change