Kouji Kozaki

Hozo: An Environment for Building/Using Ontologies Based on a Fundamental Consideration of Role and Relationship

We have developed an environment for building/using ontologies, named Hozo, based on both of a fundamental consideration of an ontological theory and a methodology of building an ontology. Since Hozo is based on an ontological theory of a role-concept, it can distinguish concepts dependent on particular contexts from so-called basic concepts and contribute to building reusable ontologies.

Construction and Deployment of a Plant Ontology

Although the necessity of an ontology and ontological engineering is well-understood, there has been few success stories about ontology construction and its deployment to date. This paper presents an activity of ontology construction and its deployment in an interface system for an oil-refinery plant operation which has been done under the umbrella of Human-Media Project for four years. It also describes the reasons why we need an ontology, what ontology we built, what environment we used for building the ontology and how the ontology is used in the system. The interface has been developed intended to establish a sophisticated technology for advanced interface for plant operators and consists of several agents. The system has been implemented and preliminary evaluation has been done successfully.

Ontology Engineering Environments

Ontology engineering is a successor of knowledge engineering and is expected to play a critical role in the next generation knowledge processing by contributing to knowledge sharing/reuse and semantic interoperability of metadata. Although the importance of ontology is well-understood, building a good ontology is a hard task. This paper discusses ontology engineering environments with comparison between them. Because of the space limitation, four environments are selected: OntoEdit, WebODE, Protege and Hozo each of which covers a wide rage of ontology development process rather than being a single-purpose tool which should be covered elsewhere. First, several key factors to evaluate ontology development environments are discussed. The stress is laid on development process-related aspects rather than static characteristics of an environment. According to the factors, each environment is briefly overviewed followed by comparison between them with a summary table.

An environment for distributed ontology development based on dependency management

This paper describes a system for supporting development of ontology in a distributed manner. By a distributed manner, we mean ontology is divided into several component ontologies, which are developed by different developers in a distributed environment. The target ontology is obtained by compiling the component ontologies. These component ontologies are identified according to their conceptual level or domain characteristics. The distributed development of ontologies applies to many situations such as cooperative development, reusing ontologies and so on. To support such a way of ontology development, we investigate the dependency between component ontologies and design some functions for management of these ontologies based on their dependencies. We next consider the influence of a change of one ontology to others through its dependencies and design a function to suggest a few candidate modifications of the influenced ontology for keeping the consistency. We also present some examples of how the system works.

The RIKEN integrated database of mammals

The RIKEN integrated database of mammals (http://scinets.org/db/mammal) is the official undertaking to integrate its mammalian databases produced from multiple large-scale programs that have been promoted by the institute. The database integrates not only RIKEN’s original databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists’ Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information.

Understanding an ontology through divergent exploration

It is important that the ontology captures the essential conceptual structure of the target world as generally as possible. However, such ontologies are sometimes regarded as weak and shallow by domain experts because they often want to understand the target world from the domain-specific viewpoints in which they are interested. Therefore, it is highly desirable to have not only knowledge structuring from the general perspective but also from the domainspecific and multi-perspective so that concepts are structured for appropriate understanding from the multiple experts. On the basis of this observation, the authors propose a novel approach, called divergent exploration of an ontology, to bridge the gap between ontologies and domain experts. Based on the approach, we developed an ontology exploration tool and evaluated the system through an experimental use by experts in an environmental domain. As a result, we confirmed that the tool supports experts to obtain meaningful knowledge for them through the divergent exploration and it contributes to integrated understanding of the ontology and its target domain.

Role organization model in hozo

The establishment of a computational framework of roles contributes effectively to the management of instance models because it provides us with a useful policy for treatment of views and contexts related to roles. In our research, we have developed an ontology building environment, which provides a framework for representation of roles and their characteristics. In this paper, as an extension of the framework, we present a framework for organizing roles according to their context dependencies. We especially focus on defining and organizing compound roles, which depend on several contexts.

Initial design process of the sustainability science ontology for knowledge-sharing to support co-deliberation

Implementation of the sustainability science (SS) approach is often difficult because of poor communication between experts from different academic fields. We focused on ontology engineering as a method of knowledge structuring that supports the co-deliberation process. However, SS is too broad for a few experts to construct an ontology because SS targets and covers almost all existing research fields from the viewpoint of problem-solving. The N-iteration process is required for completing an SS ontology. In the present paper, we discuss the initial design process for constructing an ontology on SS from the aspect of a knowledge-sharing tool to support co-deliberation. First, we identified the SS ontology by referring to the existing literature. Second, we traced the structuring process of the SS ontology, which is independent of the existing research domain. Third, we compared the SS ontology with existing ontologies or concept structures on SS. Fourth, we assessed the SS ontology produced in the initial process in terms of relevance and coverage and addressed areas for improvement in order to facilitate co-deliberation among researchers from different domains. As a result of developing the SS ontology and applying it to the mapping tool that we developed based on the ontology, we found the following three points: the SS ontology enables us to define concepts relevant to SS without overlapping by distinguishing part-of and attribute-of relationships at the upper level of the ontology; the SS-based mapping tool successfully represents the potential countermeasures required by the targeted problem for all scientific fields except experimental engineering; however, the SS ontology requires further improvement in order to represent the conceptual linkage arising from compound and secondary problems and the fulfillment of classes at the lower hierarchy of Shortage problem, and requires slots for the entire hierarchy. In addition, based on the discussion of the areas for improvement, we found that missing slots and classes should be added in the process in which we use or improve tools corresponding to a variety of requirements for supporting co-deliberation. In this way, we are able to propose an incremental process for constructing the SS ontology from the aspect of a knowledge-sharing tool to support co-deliberation.

Understanding Semantic Web Applications

Ten years have passed since the concept of the semantic web was proposed by Tim Berners-Lee. For these years, basic technologies for them such as RDF(S) and OWL were published. As a result, many systems using semantic technologies have been developed. Some of them are not prototype systems for researches but real systems for practical use. The authors analyzed semantic web applications published in the semantic web conferences (ISWC, ESWC, ASWC) and classified them based on ontological engineering. This paper is a review of application papers published in Semantic Web conferences. We discuss a trend and the future view of them using the results.

An ontological modeling approach for abnormal states and its application in the medical domain

BackgroundRecently, exchanging data and information has become a significant challenge in medicine. Such data include abnormal states. Establishing a unified representation framework of abnormal states can be a difficult task because of the diverse and heterogeneous nature of these states. Furthermore, in the definition of diseases found in several textbooks or dictionaries, abnormal states are not directly associated with the corresponding quantitative values of clinical test data, making the processing of such data by computers difficult.ResultsWe focused on abnormal states in the definition of diseases and proposed a unified form to describe an abnormal state as a “property,” which can be decomposed into an “attribute” and a “value” in a qualitative representation. We have developed a three-layer ontological model of abnormal states from the generic to disease-specific level. By developing an is-a hierarchy and combining causal chains of diseases, 21,000 abnormal states from 6000 diseases have been captured as generic causal relations and commonalities have been found among diseases across 13 medical departments.ConclusionsOur results showed that our representation framework promotes interoperability and flexibility of the quantitative raw data, qualitative information, and generic/conceptual knowledge of abnormal states. In addition, the results showed that our ontological model have found commonalities in abnormal states among diseases across 13 medical departments.