An ontology is a model language that supports the functions to integrate conceptually distributed domain knowledge and infer relationships among the concepts. Ontologies are developed based on the target domain knowledge. As a result, methodologies to automatically generate an ontology from metadata that characterize the domain knowledge are becoming important. However, existing methodologies to automatically generate an ontology using metadata are required to generate the domain metadata in a predetermined template, and it is difficult to manage data that are increased on the ontology itself when the domain OWL (Ontology Web Language) individuals are continuously increased. The database schema has a feature of domain knowledge and provides structural functions to efficiently process the knowledge-based data. In this paper, we propose a methodology to automatically generate ontologies and manage the OWL individual through an interaction of the database and the ontology. We describe the automatic ontology generation process with example schema and demonstrate the effectiveness of the automatically generated ontology by comparing it with existing ontologies using the ontology quality score.

With the emergence of various forms of smart devices and new paradigms such as the Internet of Things (IoT) concept, the IT (Information Technology) service areas are expanding explosively compared to the provision of services by single systems. A new system operation concept that has emerged in accordance with such technical trends is the IT ecosystem. The IT ecosystem can be considered a special type of system of systems in which multiple systems with various degrees of autonomy achieve common goals while adapting to the given environment. The single systems that participate in the IT ecosystem adapt autonomously to the current situation based on collected data from sensors. Furthermore, to maintain the services supported by the whole IT ecosystem sustainably, the configuration of single systems that participate in the IT ecosystem also changes appropriately in accordance with the changed situation. In order to support the IT ecosystem, this paper proposes an architecture framework that supports dynamic configuration changes to achieve the goal of the whole IT ecosystem, while ensuring the autonomy of single systems through the collection of data from sensors so as to recognize the situational context of individual participating systems. For the feasibility evaluation of the proposed framework, a simulated example of an IT ecosystem for unmanned forest management was constructed, and the quantitative evaluation results are discussed in terms of the extent to which the proposed architecture framework can continuously provide sustainable services in response to diverse environmental context changes.

The Conventional Cloud Common Data Model (CDM) uses a centralized method of user identification and credentials. This needs to be solved in a decentralized way because there are limitations in interoperability such as closed identity management and identity leakage. In this paper, we propose a DID (Decentralized Identifier)-based cloud CDM that allows researchers to securely store medical research information by authenticating their identity and to access the CDM reliably. The proposed service model is used to provide the credential of the researcher in the process of creating and accessing CDM data in the designed secure cloud. This model is designed on a DID-based user-centric identification system to support the research of enrolled researchers in a cloud CDM environment involving multiple hospitals and laboratories. The prototype of the designed model is an extension of the encrypted CDM delivery method using DID and provides an identification system by limiting the use cases of CDM data by researchers registered in cloud CDM. Prototypes built for agent-based proof of concept (PoC) are leveraged to enhance security for researcher use of ophthalmic CDM data. For this, the CDM ID schema and ID definition are described by issuing IDs of CDM providers and CDM agents, limiting the IDs of researchers who are CDM users. The proposed method is to provide a framework for integrated and efficient data access control policy management. It provides strong security and ensures both the integrity and availability of CDM data.

Public healthcare has transformed from treatment to preventive care and disease management. The Common Data Model (CDM) provides a standard data structure defined to utilize hospitals’ data. Digital identity takes a significant role as the body of information about an individual used by computer systems to identify and establish trust among organizations. The CDM research network, composed of users handling medical information, has several digital identities associated with their activity. A high central authority cost can be reduced by Distributed Ledger Technology (DLT). It enables users to control their identities independently of a third party. To preserve the privacy of researchers in clinical studies, secure identification is the main concern of identifying the researcher and its agents. To do so, they should pose a legally verifiable credential in the cloud CDM. By presenting the proof represented by the capability that the user has, each identity has access control that is linked to an authentication credential that the cloud CDM can verify. Assurance in one’s identity is confirmed by asserting claims with the identity and its capability, providing its verifiable credential to the authentication entity in the cloud CDM. This paper describes the user-centric claim-based identity operation model based on use cases to handle researcher identity in the cloud CDM. In this model, credentials are designed as a capability and presented to them to access SPs in the cloud CDM. To provide well-controlled access control in the cloud CDM, we build and prototype a capability based CDM management system.

Cloud computing has emerged as more than just a piece of technology, it is rather a new IT paradigm. The philosophy behind cloud computing shares its view with green computing where computing environments and resources are not as subjects to own but as subjects of sustained use. However, converting currently used IT services to Software as a Service (SaaS) cloud computing environments introduces several new risks. To mitigate such risks, existing software development processes must undergo significant remodeling. This study analyzes actual cases of SaaS cloud computing environment adoption as a way to derive four new best practices for software development and incorporates the identified best practices for currently-in-use processes. Furthermore, this study presents a design for generic software development processes that implement the proposed best practices. The design for the generic process has been applied to reinforce the weak points found in SaaS cloud service development practices used by eight enterprises currently developing or operating actual SaaS cloud computing services. Lastly, this study evaluates the applicability of the proposed SaaS cloud oriented development process through analyzing the feedback data collected from actual application to the development of a SaaS cloud service Astation.