Ontology-based Knowledge Model Research Articles

Review of Computer Aided Product Innovation Design Based on Knowledge

Design knowledge acquisition, representation and application are key technologies in computer-aided innovation design. It is an important way to improve the innovation capability and core competitiveness of manufacturing enterprises. The present state of the art of theories and tools of computer-aided product innovation design was presented, some key technologies and problems of the computer-aided product innovation design based on knowledge were summarized and analyzed. It was proposed that the ontology-based knowledge modeling based on design process was the base of computer-aided innovation design, The efficient and precise ontology matching method is seeked to efficiently support updating design knowledge by synthetically considering the concept semantics and concept hierarchy structure, and the knowledge association and concept semantic retrieval and reasoning can be better realized by taking into full consideration of semantic relationships of between design knowledges.

Ontology-based Knowledge Modeling for Using Physical Effects

Su-Field analysis, as one of the inventive problem solving tools, can be used to analyse and improve the efficacy of the technical system. Generally, the process of using Su-Field model to solve a specific inventive problem includes: building a Problem Model, mapping to a Generic Problem Model, finding a Generic Solution Model based on the corresponding inventive standard, and finally establishing and instantiating a Solution Model. As one of the most important phases of Su-Field analysis, the last step is normally implemented manually with the help of physical effects, which link generic technical functions with specific applications and systems. The physical effects compatible with the context of the specific problem should be chosen to assist the users to instantiate the Solution Model. However, the physical effects and the specific problems are built at different levels of abstraction, and it is difficult for the users to choose, that is, given a certain function, too many physical effects are chosen while with the detailed context of the problem, no physical effect is returned. This paper firstly proposes a new way of representing physical effects using the change of two states, that is, the couple of two states before and after applying physical effects. Then, the knowledge about using physical effects is formalized in OWL (Ontology Web Language) - an ontology language for semantic web, and the constraint knowledge, such as the condition to use each kind of physical effect, is formalized in SWRL (Semantic Web Rule Language) - a rule language. Finally, the reasoning process of using physical effects is performed with the support of JESS (Java Expert System Shell) rule engine.

Ontology for real estate cadastre

Standardisation efforts in the geospatial domain, provided by ISO TC 211 and OpenGIS Consortium, have brought many specifications and standards that define structure and encoding rules of data and interfaces of services. These standards provide syntactic interoperability of geospatial data and services, while neglecting their semantics. In order to achieve semantic interoperability, i.e. explicitly define the meaning of data and services to make them understandable both to machines and humans, there are attempts to develop Geospatial Semantic Web, where semantics of data will be expressed explicitly and formally. An important part of this process is the development of domain ontologies, i.e. a common vocabulary in some domain. In order to bring semantics into cadastral systems, it is necessary to develop ontology for real estate cadastre. Therefore, the authors propose the ontology based knowledge model in the field of real estate cadastre based on ISO 19152 international standard and other geospatial standards, as a core ontology for cadastre on top of which a domain ontology for a specific country should be built. The domain ontology presented in this paper refers to the real estate cadastre of Serbia, but a similar approach can be adopted for different cadastral organisations in other countries. In this way, different domain ontologies based on various cadastral organisations will conform to the same standard based core ontology that will provide a basis for the semantic search and integration of cadastral data on national and international level.

Ontology-Based Knowledge Model for Multi-View KDD Process

Knowledge Discovery in Databases (KDD) is a highly complex, iterative and interactive process that involves several types of knowledge and expertise. In this paper the authors propose to support users of a multi-view analysis (a KDD process held by several experts who analyze the same data with different viewpoints). Their objective is to enhance both the reusability of the process and coordination between users. To do so, they propose a formalization of viewpoint in KDD and a Knowledge Model that structures domain knowledge involved in a multi-view analysis. The authors’ formalization, using OWL ontologies, of viewpoint notion is based on CRISP-DM standard through the identification of a set of generic criteria that characterize a viewpoint in KDD.

Design Knowledge Origin Characteristics and Classification

In this paper, we established the methods to classify and represent the concept-design knowledge and developed an ontology-based model presenting the design knowledge as well as a model for modeling cycles. We further applied these methods and models to develop a specific ontology-based design knowledge model and validated them in the management system of design knowledge for the construction machinery.

Study on an Ontology-Based Design Knowledge Modeling Algorithm

In this paper, we concentrate on the ontology-Based design knowledge modeling technologies for the construction machinery. For that, we study the ontology modeling theory, the representation of product design knowledge and the ontology modeling of design knowledge, etc. From the design knowledge management’s angle, design knowledge modeling approach is studied to support the design knowledge development, transfer and reuse for the construction machinery.

Design and Implementation of an Ontology-Based Clinical Reminder System to Support Chronic Disease Healthcare

Improving quality of healthcare for people with chronic conditions requires informed and knowledgeable healthcare providers and patients. Decision support and clinical information system are two of the main components to support improving chronic care. In this paper, we describe an ontology-based information and knowledge management framework that is important for chronic disease care management. Ontology-based knowledge acquisition and modeling based on knowledge engineering approach provides an effective mechanism in capturing expert opinion in form of clinical practice guidelines. The framework focuses on building of healthcare ontology and clinical reminder system that link clinical guideline knowledge with patient registries to support evidenced-based healthcare. We describe implementation and approaches in integrating clinical reminder services to existing healthcare provider environment by focusing on augmenting decision making and improving quality of patient care services.

An Ontology-Based Design Knowledge Model for the Construction Machinery

In this paper, we investigated the knowledge modeling and proposed an ontology-based descriptively-logic theory using fuzzy interval in order to support the management and re-usage of the knowledge of design. We also established the methods to classify and present the concept-design knowledge and developed an ontology-based model presenting the knowledge of design as well as a model for modeling cycles. We further applied these methods and models to develop a specific ontology-based design-knowledge model and At last the practicability and validity of these methods are validated in the management system of design knowledge for the construction machinery.

Ontology-Based Knowledge Modeling for Collaborative Product Development

The process of Collaborative Product Development (CPD) comprises highly creative and knowledge-intensive tasks that involve extensive information exchange and communication among distributed teams. Traditional information management systems fail to provide adequate capability to support CPD, due to their inflexible data structures and hard-wired usage procedures, as well as their restricted ability to integrate process and product information. An ontology-based method of knowledge management is proposed to support CPD. The key idea hiding in the method is a flexible ontology-based schema with formally defined semantics that enables the capture and reuse of design knowledge. A part of CPD-oriented ontology library represented by UML is displayed.

Study on Product Customization Design Knowledge Framework Based on Ontology

In this paper, we concentrate on the ontology-Based design knowledge modeling technologies for the product form. For that, we study the ontology modeling theory, the representation of product design knowledge. From the view of the DKM, the product form prototype and its mathematical model will be established for Product Forms Innovative Design System (FIDS).

Knowledge integration and sharing for collaborative molding product design and process development

This study presents a systematic approach to developing a knowledge integration and sharing mechanism for collaborative molding product design and process development. The proposed approach includes the steps of (i) collaborative molding product design and process development process modeling, (ii) an ontology-based knowledge model establishment, (iii) knowledge integration and sharing system framework design, (iv) ontology-based knowledge integration and sharing methods development, and (v) ontology-based knowledge integration and sharing mechanism implementation. The mechanism can support collaborative molding product design and process development by providing functions of knowledge integration and sharing. Results of this study facilitate the knowledge integration and sharing of collaborative molding product design and process development to satisfy the product knowledge demands of participants, and thus increase molding product development capability, reduce molding product development cycle time and cost, and ultimately increase molding product marketability.