In this task, we design and develop an ontology model for providing personalized, context-aware services for American Indian (AI) users in mobile environments. Central to the approach is the use of ontological user profile modeling which captures various characteristics of an AI user (including socio-economic, cultural, ethnical, and geographical aspects of AI patients) in order to create a unique set of profile information. The domain we consider in this project includes the wellbeing and lifestyle of AI diabetic patients. Several different types of knowledge contribute to the domain: knowledge about workout, food and nutrition, and knowledge about patients’ context including physical, social, and cultural context.
The interdisciplinary social and scientific nature of this research requires the use of an integrated approach. We develop this ontology through a collaborative process that includes domain experts, and ontology engineering experts.
As there are many synergies between software engineering and ontology development, we adopt some idea of the systems development life cycle of software engineering to our ontology development life cycle. In our design, we divide the ontology development cycle into six work phases. The ontology engineers, developers and domain expert plan for, develop, implement, evaluate and deliver ontology based on these six phases. As shown in Fig. 1, the ontology development process is recurring in cycles, as each work phase will be cyclically and incrementally repeated. At each new cycle the ontology will be further revise and refined. Different personnel (domain experts, ontology engineers, and final users) get involved in different phases.
Currently, we have defined our initial version of the ontology. Details of the current development of the ontology can be found in our recent publication:
We are continuing to revise and enrich the ontology according to our new discovery and understanding of this domain.