Ubiquitous computing is necessary to define models for broad contextual information arising out of surrounding environment. It also helps comprehend how to model a mechanism of selectively collecting useful pieces of contextual information and of providing relevant intelligent services. Further, studies are also required on how to process contextual information, its maintenance, and reasoning. However, current context-aware researches are still in need of modeling techniques reflecting ontological characteristics. As a result, it is impossible to effectively provide relevant intelligent services. They are limited as well in terms of contextual reasoning and interoperability across different pieces of contextual information. Aware of the issues, this study proposes an ontology-based context-aware modeling technique, along with a relevant framework, in order to enable efficient specification of contextual information and, thereby, further to provide intelligent context-aware services for context management and reasoning. Moreover, we mobilize the maxim of "five Ws and one H" to process physical and logical contextual information and to support our proposed technique. The maxim-applied modeling technique sets forth an intuitive context-aware schema and demonstrates high applicability to sharing and integration of contextual information. Meanwhile, the ontology-based modeling supports reasoning on contextual information and facilitates more intelligent and reliable services.

When sharing and storing healthcare data in a cloud environment, access control is a central issue for preserving data privacy as a patient's personal health data may be accessed without permission from many stakeholders. Specifically, dynamic authorization for the access of data is required because personal health data is stored in cloud storage via wearable devices. Therefore, we propose a dynamic access control model for preserving the privacy of personal healthcare data in a cloud environment. The proposed model considers context information for dynamic access. According to the proposed model, access control can be dynamically determined by changing the context information; this means that even for a subject with the same role in the cloud, access permission is defined differently depending on the context information and access condition. Furthermore, we experiment the ability of the proposed model to provide correct responses by representing a dynamic access decision with real-life personalized healthcare system scenarios.

SUMMARYMetadata registry (MDR) is based on the international standard ISO/IEC 11179. The committee of ISO/IEC JTC 1/SC 32, which had standardized the MDR, has started to improvise the MDR, and the improvised version is named extended MDR (XMDR). However, the XMDR does not fully support the ontology concept, and no method is available for mapping ontology registrations onto registries. To overcome the limitations of the outdated XMDR, this paper proposes an extended XMDR (XMDR+) framework. The XMDR+ framework provides a method for mapping of ontology registrations between the metadata registry and ontologies. To improve the functions of the XMDR, we have proposed herein a framework that is capable of defining a model that manages the relations not only among ontological concepts but also among instances, and guarantees the management and storage of their relationships for supporting valid relations of the ontologies.