A collaborative methodology for tacit knowledge management: Application to scientific research

Tacit knowledge, which refers to the know-how, is critical to understand and reuse since it is located in the human heads. It represents the foremost element for human and team evaluation. Seeking for tacit knowledge is achieved only by communicating with the concerned persons, which makes losing it axiomatic if people leave their work without documenting their know-how. Thus, providing a collaborative environment based on a common conceptualization of the domain to formalize the experts’ knowledge and to share their outcomes is required. However, some barriers pertaining to cultural and social factors such as personality traits impede capturing the conceptual model. To cope with these issues, we have proposed a generic two-step methodology that copes with human barriers when capturing the domain experts’ tacit knowledge, their skills, and seeds terms in order to converge to a common knowledge representation. Considering the scientific research management as a use case, we followed the proposed methodology to formalize our scientific research knowledge in the context of network and communication research field. Based on the generated ontology, we have developed a semantic web platform that allows collaboratively annotating experts’ knowledge in a computer interpretable format that can be shared and reused by human and machines. Our evaluation is based on end users’ quality of experience and feedbacks.     

A cooperative tool for facilitating knowledge management

Nowadays, we can find systems and environments supporting processes of ontology building. However, these processes have not been specified enough yet. In this work, a real environment for integrating ontologies supplied by a predetermined set of (experts) users, who might be distributed through a communication network and working cooperatively in the integration process, is introduced. In this environment, the (expert) user can check for the ontology that is being produced, so he/she is able to refine his/her private ontology. Furthermore, the experts who take part of the ontology construction process are allowed to use their own terminology even for requesting information about the global-derived ontology until a specific instant after the integration.     

An ontology-based knowledge framework for engineering material selection

Engineering material selection intensively depends on domain knowledge. In the face of the large number and wide variety of engineering materials, it is very necessary to research and develop an open, shared, and scalable knowledge framework for implementing domain-oriented and knowledge-based material selection. In this paper, the fundamental concepts and relationships involved in all aspects of material selection are analyzed in detail. A novel ontology-based knowledge framework is presented. The ontology-based Semantic Web technology is introduced into the semantic representation of material selection knowledge. The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge. A knowledge retrieval and reasoning approach integrating ontology concepts, instances, knowledge rules, and semantic queries encoded with Query-enhanced Web Rule Language (SQWRL) is proposed. The presented knowledge framework can provide powerful knowledge services for material selection. Finally, based on this knowledge framework, a case study on constructing a mold material selection knowledge system is provided. This work is a new attempt to build an open and shared knowledge framework for engineering material selection.     

Knowledge sharing in virtual enterprises via an ontology-based access control approach

Collaborating throughout a product life cycle via virtual enterprise (VE) is one of the most promising strategies for enhancing global competitiveness. Efficient and secure knowledge sharing is critical to the success of a VE. This study presents a novel approach, model and technology for knowledge access control and sharing across enterprises. First, this study proposes an ontology-based knowledge sharing model and a multiple-layer knowledge representation framework on which a knowledge access control model for knowledge sharing in a VE is proposed. In the proposed model, user authorizations permitting access to knowledge in a VE are classified into two levels: (1) basic privileges and (2) extended privileges. The former is evaluated from four dimensions, i.e. who, what, when and where, while the latter is determined by considering how three domain ontologies, i.e., product, organization and activity, are related. This study then develops a knowledge access control policy (KACP) language model which is used to identify the knowledge access control and sharing rules of a VE and all its enterprise members. The knowledge access control model proposed in this study can facilitate VE Knowledge management and sharing across enterprises, enhance knowledge sharing security and flexibility and regulate knowledge sharing to expeditiously reflect changes in the business environment.     

一种支持软件知识共享的本体模型研究

为了支持分布式环境下项目团队成员之间软件开发知识有效的共享,需要对软件开发知识以及它们之间的关系进行分析和定义。根据软件开发知识的内容、特点以及它们之间的关系,对软件开发知识进行了形式化的表示,并创建了软件开发知识本体和软件开发知识本体规则。通过protégé 和Jena实现对此本体的创建、存储和对此本体规则的SPARQL形式转换,据此形成知识本体库来支持软件开发知识共享。     

Analyzing multilingual knowledge innovation in patents

In the process of analyzing knowledge innovation, it is necessary to identify the existing boundaries of knowledge so as to determine whether knowledge is new – outside these boundaries. For a patent to be granted, all aspects of the patent request must be studied to determine the patent innovation. Knowledge innovation for patent requests depends on analyzing current state of the art in multiple languages. Currently the process is usually limited to the languages and search terms the patent seeker knows. The paper describes a model for representing the patent request by a set of concepts related to a multilingual knowledge ontology. The search for patent knowledge is based on Fuzzy Logic Decision Support and allows a multilingual search. The model was analyzed using a twofold approach: a total of 104,296 patents from the United States Patent and Trademark Office were used to analyze the patent extraction process, and patents from the Korean, US, and Chinese patent offices were used in the analysis of the multilingual decision process. The results display high recall and precision and suggest that increasing the number of languages used only has minor effects on the model results.     

Adapting domain ontology for personalized knowledge search and recommendation

This paper presents research on the development of a domain ontology adaptation system for personalized knowledge search and recommendation that adapts a suitable domain ontology according to the previous browsing and reading behavior of users (i.e., usage history log). An adaptive domain ontology can satisfy the future requirements of users and promote use value. In developing the system, a domain ontology adaptation model is first designed. Based on the designed adaptation model, a methodology for domain ontology adaptation is developed. Subsequently, a domain ontology adaptation system is implemented with an illustrative example of securities trading. Finally, a system evaluation for user satisfaction and a methodology evaluation are conducted to demonstrate that the developed methodology and system worked efficiently.     

An ontology-based support for product conceptual design

The research presented in this paper is a follow-up of our prior work involving the development of a graphical modeling tool to support designers at the conceptual design stage. To close the loop for supporting designers in generating design concepts flexibly, fast, and easily, an ontology-based approach for knowledge management that works along with the graphical modeling tool is discussed. Ontology and databases for the tool are developed to promote the systematic capture of design knowledge and efficient reuse of the design knowledge selection. In order to locate the proper information and query the data from the databases, the relationship between the ontology and databases, the data analysis process, ontology enrichment, and the ontology-based query engine are built to offer users multiple design results according to users’ requirements. A tire design example is presented to demonstrate the proposed approach. The ontology-based method described in this paper can help retrieve and save the complex relations, support the reasoning, integrate heterogeneous data resources and offer users more accurate, proper and comprehensive data.     

Supply chain management ontology from an ontology engineering perspective

Knowledge sharing and reuse are important factors affecting the performance of supply chains. These factors can be amplified in information systems by supply chain management (SCM) ontology. The literature provides various SCM ontologies for a range of industries and tasks. Although many studies make claims of the benefits of SCM ontology, it is unclear to what degree the development of these ontologies is informed by research outcomes from the ontology engineering field. This field has produced a set of specific engineering techniques, which are supposed to help developing quality ontologies. This article reports a study that assesses the adoption of ontology engineering techniques in 16 SCM ontologies. Based on these findings, several implications for research as well as SCM ontology adoption are articulated.     

Users’ attitudes toward Web-based collaborative learning systems for knowledge management

The Web-based technology is a potential tool for supported collaborative learning that may enrich learning performance, such as individual knowledge construction or group knowledge sharing. Thus, understanding Web-based collaborative learning for knowledge management is a critical issue. The present study is to investigate learners’ attitudes toward Web-based collaborative learning systems. Based on this research, the results of factor analysis show that five attitude factors (system functions, system satisfaction, collaborative activities, learners’ characteristics, and system acceptance) should be examined at the same time when building a Web-based collaborative learning system. The results also provide an acceptance model for understanding users’ behavioral intention of facilitating Web-based collaborative systems.     

A knowledge engineering approach to knowledge management

Knowledge management facilitates the capture, storage, and dissemination of knowledge using information technology. Methods for managing knowledge have become an important issue in the past few decades, and the KM community has developed a wide range of technologies and applications for both academic research and practical applications. In this paper, we propose a knowledge engineering approach (KMKE) to knowledge management. First, a knowledge modeling approach is used to organize and express various types of knowledge in a unified knowledge representation. Second, a verification mechanism is used to verify knowledge models based on the formal semantics of the knowledge representation. Third, knowledge models are classified and stored in a hierarchical ontology system. Fourth, a knowledge query language is designed to enhance the dissemination of knowledge. Finally, a knowledge update process is applied to modify the knowledge storage with respect to users’ needs. A knowledge management system for computer repair is used as an illustrative example.     

A multilingual knowledge management system: A case study of FAO and WAICENT

This paper provides a case study of a multilingual knowledge management system for a large organization. In so doing we elicit what it means for a system to be “multilingual” and how that changes some previous research on knowledge management. Some researchers have viewed multilingual as meaning a multilingual user interface. However, that is only a small part of the story. In this case we find multilingual also refers to a broad range of “multilingual,” including multilingual knowledge resources, multilingual feedback from users, multilingual search, multilingual ontologies and other concerns.     

Security as a contributor to knowledge management success

Security is an important topic, but is it important for Knowledge Management (KM)? To date, little mainstream KM research is coming through with a security focus. This paper asks why, and proposes that security be integrated into KM success models. The Jennex and Olfman (International Journal of Knowledge Management 2(3):51–68, 2006) KM success model is used to illustrate how security, specifically risk management, and the National Security Telecommunications and Information System Security Committee (NSTISSC) security model can be applied to KM management support and governance and KM Strategy. Finally, two case studies are provided that illustrate the application of risk management through governance to KM.     

Using ontology-based text classification to assist Job Hazard Analysis

The dangers of the construction industry due to the risk of fatal hazards, such as falling from extreme heights, being struck by heavy equipment or materials, and the possibility of electrocution, are well known. The concept of Job Hazard Analysis is commonly used to mitigate and control these occupational hazards. This technique analyzes the major tasks in a construction activity, identifies all potential task-related hazards, and suggests safe approaches to reduce or avoid each of these hazards. In this paper, the authors explore the possibility of leveraging existing construction safety resources to assist JHA, aiming to reduce the level of human effort required. Specifically, the authors apply ontology-based text classification (TC) to match safe approaches identified in existing resources with unsafe scenarios. These safe approaches can serve as initial references and enrich the solution space when performing JHA. Various document modification strategies are applied to existing resources in order to achieve superior TC effectiveness. The end result of this research is a construction safety domain ontology and its underlying knowledge base. A user scenario is also discussed to demonstrate how the ontology supports JHA in practice.     

Building ontology based knowledge maps to assist business process re-engineering

Business Process Re-engineering (BPR) is being used to improve the efficiency of the organizational processes, however, a number of obstacles have prevented its full potential from being realised. One of these obstacles is caused by an emphasis on the business process itself at the exclusion of considering other important knowledge of the organization. Another is due to the lack of tools for identifying the cause of the inefficiencies and inconsistencies in BPR. In this paper we propose a methodology for BPR that overcomes these two obstacles through the use of a formal organizational ontology and knowledge structure and source maps. These knowledge maps are represented formally to facilitate an inferencing mechanism which helps to automatically identify the causes of the inefficiencies and inconsistencies. We demonstrate the applicability of this methodology through the use of a case study of a university domain.     

A knowledge grid model and platform for global knowledge sharing

This paper proposes a knowledge grid model for sharing and managing globally distributed knowledge resources. The model organizes knowledge in a three-dimensional knowledge space, and provides a knowledge grid operation language, KGOL. Internet users can use the KGOL to create their knowledge grids, to put knowledge to them, to edit knowledge, to partially or wholly open their grids to all or some particular grids, and to get the required knowledge from the open knowledge of all the knowledge grids. The model enables people to conveniently share knowledge with each other when they work on the Internet. A software platform based on the proposed model has been implemented and used for knowledge sharing in research teams.     

Architecture for knowledge discovery and knowledge management

In this paper, we propose I-MIN model for knowledge discovery and knowledge management in evolving databases. The model splits the KDD process into three phases. The schema designed during the first phase, abstracts the generic mining requirements of the KDD process and provides a mapping between the generic KDD process and (user) specific KDD subprocesses. The generic process is executed periodically during the second phase and windows of condensed knowledge called knowledge concentrates are created. During the third phase, which corresponds to actual mining by the end users, specific KDD subprocesses are invoked to mine knowledge concentrates. The model provides a set of mining operators for the development of mining applications to discover and renew, preserve and reuse, and share knowledge for effective knowledge management. These operators can be invoked by either using a declarative query language or by writing applications.The architectural proposal emulates a DBMS like environment for the managers, administrators and end users in the organization. Knowledge management functions, like sharing and reuse of the discovered knowledge among the users and periodic updating of the discovered knowledge are supported. Complete documentation and control of all the KDD endeavors in an organization are facilitated by the I-MIN model. This helps in structuring and streamlining the KDD operations in an organization.     

Reuse of knowledge assets from repositories: A mixed methods study

Reuse of information retrieved from an electronic knowledge repository and how this complements person-to-person interactions are poorly understood. I developed a research model that examined factors influencing how individuals benefit from reuse of knowledge assets. Using a mixed method approach, two empirical studies were conducted to test the model. The results showed that two key factors helped users to overcome difficulties in reusing knowledge assets: seeking assistance from and sharing a common perspective with the author of the asset. The study explains when and how individuals receive benefits from knowledge reuse. When individuals reuse complex knowledge assets in domains with which they are unfamiliar, they apparently gain more benefit by contacting the author; sharing a common perspective with the author also facilitates asset reuse. Thus both electronic repositories and person-to-person interaction mechanisms complement one another in facilitating knowledge sharing.     

Using a simulation model for knowledge elicitation and knowledge management

The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process.This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself.     

An ontology-based fuzzy decision support system for multiple sclerosis

The use of Magnetic Resonance (MR) as a supporting tool in the diagnosis and monitoring of multiple sclerosis (MS) and in the assessment of treatment effects requires the accurate determination of cerebral white matter lesion (WML) volumes. In order to automatically support neuroradiologists in the classification of WMLs, an ontology-based fuzzy decision support system (DSS) has been devised and implemented. The DSS encodes high-level, specialized medical knowledge in terms of ontologies and fuzzy rules and applies this knowledge in conjunction with a fuzzy inference engine to classify WMLs and to obtain a measure of their volumes. The performance of the DSS has been quantitatively evaluated on 120 patients affected by MS. Specifically, binary classification results have been first obtained by applying thresholds on fuzzy outputs and then evaluated, by means of ROC curves, in terms of trade-off between sensitivity and specificity. Similarity measures of WMLs have been also computed for a further quantitative analysis. Moreover, a statistical analysis has been carried out for appraising the DSS influence on the diagnostic tasks of physicians. The evaluation has shown that the DSS offers an innovative and valuable way to perform automated WML classification in real clinical settings.