Ontology versioning in an ontology management framework

Ontologies have become ubiquitous in information systems. They constitute the semantic Web's backbone, facilitate e-commerce, and serve such diverse application fields as bioinformatics and medicine. As ontology development becomes increasingly widespread and collaborative, developers are creating ontologies using different tools and different languages. These ontologies cover unrelated or overlapping domains at different levels of detail and granularity. A uniform framework, which we present here, helps users manage multiple ontologies by leveraging data and algorithms developed for one tool in another. For example, by using an algorithm we developed for structural evaluation of ontology versions, this framework lets developers compare different ontologies and map similarities and differences among them. Multiple-ontology management includes these tasks: maintain ontology libraries, import and reuse ontologies, translate ontologies from one formalism to another, support ontology versioning, specify transformation rules between different ontologies and version, merge ontologies, align and map between ontologies, extract an ontology's self-contained parts, support inference across multiple ontologies, support query across multiple ontologies.     

Transactions and versioning in an ODBMS

Versant Object Technology builds and sells a distributed Object Database Management System (ODBMS), called VERSANT. This position paper proposes transaction model and version model requirements in support of the kinds of distributed database processing that ODBMS applications require. Transaction model requirements address the long transactions required by many ODBMS applications, as well as the short transactions found in conventional DBMS products. Version model requirements suggest a minimal set of primitives which can be extended to support emerging standards and companies' specific models.     

A framework to integrate design knowledge reuse and requirements management in engineering design

This paper presents a framework to integrate requirements management and design knowledge reuse. The research approach begins with a literature review in design reuse and requirements management to identify appropriate methods within each domain. A framework is proposed based on the identified requirements. The framework is then demonstrated using a case study example: vacuum pump design. Requirements are presented as a component of the integrated design knowledge framework. The proposed framework enables the application of requirements management as a dynamic process, including capture, analysis and recording of requirements. It takes account of the evolving requirements and the dynamic nature of the interaction between requirements and product structure through the various stages of product development.     

Supporting ontology adaptation and versioning based on a graph of relevance

Ontologies recently have become a topic of interest in computer science since they are seen as a semantic support to explicit and enrich data-models as well as to ensure interoperability of data. Moreover, supporting ontology adaptation becomes essential and extremely important, mainly when using ontologies in changing environments. An important issue when dealing with ontology adaptation is the management of several versions. Ontology versioning is a complex and multifaceted problem as it should take into account change management, versions storage and access, consistency issues, etc. The purpose of this paper is to propose an approach and tool for ontology adaptation and versioning. A series of techniques are proposed to ‘safely’ evolve a given ontology and produce a new consistent version. The ontology versions are ordered in a graph according to their relevance. The relevance is computed based on four criteria: conceptualisation, usage frequency, abstraction and completeness. The techniques to carry out the versioning process are implemented in the Consistology tool, which has been developed to assist users in expressing adaptation requirements and managing ontology versions.     

Causal design knowledge: Alternative representation method for product development knowledge management

This paper presents a mathematical comparison of procedural knowledge and causal knowledge, and discusses the potential roles and feasibility of causal knowledge across product development knowledge management. Since reuse of knowledge is so important in product development, various knowledge management approaches have been introduced. Most of the product design knowledge is represented by procedural knowledge, which unfortunately requires cumbersome processes to define, and is typically inadequate for representing the kind of knowledge generated during the product development process. A causal knowledge representation, however, can help us to overcome this limitation and is an alternative formalism for representing product design knowledge. In this paper we compare the procedural and causal knowledge representations. We present the mathematical definitions of two knowledge paradigms, then mathematically describe the relationship between the two. Both knowledge paradigms are then compared based on the perspective of knowledge expression, decision alternative representation, reasoning capability, and knowledge cultivation. This paper concludes that causal knowledge representation is superior to procedural knowledge representation based on the four perspectives. Finally, the knowledge systems are modeled using Systems Modeling Language (SysML), and we present a case study that demonstrates the causal knowledge features using a realistic example from industry.     

A framework for fuzzy knowledge based control

Two major problems appear during the design of a framework. The first is related to synthesizing generic elements for a family of applications and connecting them to an integrated control flow. The second lies in the design of a powerful, modular, reliable architecture that is easy to (re)use and understand. The fact of including design patterns in the architecture of frameworks minimizes the second problem. Indeed, design patterns provide proven, flexible, well‐engineered design solutions at a higher abstraction level than classes. Their associated documentation records information from experienced object‐oriented designers about solutions to recurrent problems, about contexts in which the patterns are applicable, about forces involved and consequences related to their use. This paper presents a number of the benefits of integrating design patterns in the development of an object‐oriented framework related to fuzzy logic control. It also reports on an object‐oriented design for Fuzzy Knowledge Based Control (FKBC) that includes design patterns to facilitate the development, maintenance and documentation of the FKBC framework. Copyright © 2000 John Wiley & Sons, Ltd.     

COWB: A cloud-based framework supporting collaborative knowledge management within biomedical communities

Despite the large acceptance of Semantic Web technologies and their key role in bioinformatics, some concerns begin to emerge about their suitability for supporting the requirements of collaborative environments where a research community shares and creates new knowledge. The paper discusses these concerns and proposes COWB (COllaborative Workspaces in Biomedicine), a framework which supports collaborative knowledge management in the context of biomedical communities. COWB is grounded on a multi-layer ontology-centric model. It harnesses both the semantic knowledge captured from ontologies and the functional knowledge about resources which extend the domain knowledge and support its management. Public and private workspaces provide an accessible representation of the collective knowledge that is incrementally created and allow the knowledge to cross the boundaries of closed local information. The paper presents the deployment of COWB in a cloud platform which severely curtails issues associated with scalability and performance. The paper shows the suitability of the proposed approach and aims to suggest how exploiting the potential of the Semantic Web technologies in the context of emergent technologies including Web 2.0, NoSQL databases and the cloud paradigm.     

Automatic refinement of knowledge bases with fuzzy rules

The knowledge-acquisition bottleneck obstructs the development of expert systems. Refinement of existing knowledge bases is a subproblem of the knowledge-acquisition problem. The paper presents a HEuristic REfinement System (HERES), which refines rules with mixed fuzzy and nonfuzzy concepts represented in a variant of the rule representation language Z-II automatically. HERES employs heuristics and analytical methods to guide its generation of plausible refinements. The functionality and effectiveness of HERES are verified through various case studies. It has been verified that HERES can successfully refine knowledge bases. The refinement methods can handle imprecise and uncertain examples and generate approximate rules. In this aspect, they are better than other famous learning algorithms such as ID3^15–18, AQ11, and INDUCE^{14, 19, 20} because HERES' methods are currently unique in processing inexact examples and creating approximate rules.     

A heuristically ‘optimal’ knowledge base organization technique

SOT (self-organizing tree) is a general-purpose knowledge base organizing program which automatically computes an efficient discrimination scheme for accessing large numbers of facts, rules, etc., expressed in a slot-filler representational format. The discrimination scheme supports a variety of accessing modes, including exact, instance and template matching; and ‘best first’ and resumable search. This paper describes the organizing algorithm and the nature of the search process; and gives performance statistics for the system in several tasks.     

A framework for modeling and evaluating automatic semantic reconciliation

The introduction of the Semantic Web vision and the shift toward machine understandable Web resources has unearthed the importance of automatic semantic reconciliation. Consequently, new tools for automating the process were proposed. In this work we present a formal model of semantic reconciliation and analyze in a systematic manner the properties of the process outcome, primarily the inherent uncertainty of the matching process and how it reflects on the resulting mappings. An important feature of this research is the identification and analysis of factors that impact the effectiveness of algorithms for automatic semantic reconciliation, leading, it is hoped, to the design of better algorithms by reducing the uncertainty of existing algorithms. Against this background we empirically study the aptitude of two algorithms to correctly match concepts. This research is both timely and practical in light of recent attempts to develop and utilize methods for automatic semantic reconciliation.Received: 6 December 2002, Accepted: 15 September 2003, Published online: 19 December 2003Edited by: V. Atluri.     

A split-combination approach to merging knowledge bases in possibilistic logic

We propose an adaptive approach to merging possibilistic knowledge bases that deploys multiple operators instead of a single operator in the merging process. The merging approach consists of two steps: the splitting step and the combination step. The splitting step splits each knowledge base into two subbases and then in the second step, different classes of subbases are combined using different operators. Our merging approach is applied to knowledge bases which are self-consistent and results in a knowledge base which is also consistent. Two operators are proposed based on two different splitting methods. Both operators result in a possibilistic knowledge base which contains more information than that obtained by the t-conorm (such as the maximum) based merging methods. In the flat case, one of the operators provides a good alternative to syntax-based merging operators in classical logic. This paper is a revised and extended version of [36].     

A systems thinking framework for knowledge management

Myriad frameworks have been developed for knowledge management. However, the field has been slow in formulating a generally accepted, comprehensive framework for knowledge management. This paper reviews the existing knowledge management frameworks and provides suggestions for what a general framework should include. The distinguishing feature of this research is that it emphasizes placing knowledge management in a larger context of systems thinking so that the influencing factors on its success or failure can better be recognized and understood.     

A web services framework for distributed model management

Distributed model management aims to support the wide-spread sharing and usage of decision support models. Web services is a promising technology for supporting distributed model management activities such as model creation and delivery, model composition, model execution and model maintenance to fulfill dynamic decision-support and problem solving requests. We propose a web services based framework for model management (called MM-WS) to support various activities of the model management life cycle. The framework is based on the recently proposed Integrated Service Planning and Execution (ISP & E) approach for web services integration. We discuss encoding of domain knowledge (as individual models) and utilize the MM-WS framework to interleave synthesis of composite models with their execution. A prototypical implementation with an example is used to illustrate the utility of the framework to enable distributed model management and knowledge integration. Benefits and issues of using the framework to support model-based decision-making in organizational contexts are outlined.

企业知识管理及其知识仓库的解决方案

分析了知识管理的概念、内容、关键问题及其解决方案，提出了知识仓库的概念，给出了知识管理的知识仓库解决方案。     

知识管理方法论

知识管理是当代企业管理的重要概念与手段,知识管理研究的目标是对知识进行完整、有效和一致的管理。以知识生命周期为线索,通过对知识管理各个阶段知识呈现特征的研究,总结比较了各类知识管理技术的特点及其适用范围,并着重对广义学习和广义计算在知识管理中的作用做了较为深入的讨论。最后通过对知识管理技术和方法的比较研究,简要分析概括了知识管理的基本理论与基本方法。     

Framework of knowledge management in education based on knowledge grid

Knowledge grid is a kind of knowledge sharing environment based on the World Wide Web, and its essence is the synergy and sharing of internet knowledge resource and knowledge service. KM （knowledge management） in education based on KG （knowledge grid） makes use of the grid technology and integrates the methods and tools of KM in Education to support the whole cycle of knowledge application. Based on the advantages of KM in Education, in this paper, we construct a service-oriented model of KM in Education in order to achieve more effective knowledge sharing and knowledge service in education.     

A decision-making model for knowledge collaboration and reuse through scientific workflow

Past, present and future, to realize the aim of product CTQS (i.e., lower cost, faster time to market, higher quality and better service) with manufacturing intelligence, few manufacturers have no longer engaged in product related production decision support problem (P-DSP). However, P-DSP solving (P-DSPS) is a multi-criteria decision-making problem, which is context sensitive in solution objects-attributes and chaos in the decision process of manufacturing knowledge collaboration and reuse. To alleviate these limitations, this paper presents a novel triple deep workflow model for P-DSPS. Driven by a wicked task query, the proposed workflow of P-DSPS (WP-DSPS) has the function to retrieve similarity-based alternatives from domain knowledge driven solution flow (KSF) and to evaluate with expert knowledge collaboration from knowledge driven decision flow (KDF) based on utility theory under the task event driven control flow (ECF) strategy and operation logic. In the view of alternative adaption, a domain knowledge ontology-based degree of similarity (DoS) determines the P-DSPS alternatives width, a utility function-based degree of decision (DoD) determines alternatives quality, and a belief-based knowledge fusion technique is used to synthesize decision conflicts with a consensus degree (CD). To support the proposed models, a workflow-based system prototype is proposed and validated in two case studies.     

基于本体的领域知识重用方法研究*

由于已有知识表示和本体知识表示并不在同一逻辑体系基础上,从知识表示层面提出了一种基于知识等价映射的知识重用方法解决对已有异构知识的重用问题。通过语义等价提取、在本体指导下的一致性处理以及语义映射解决了本体构建过程中对已有知识的自动重用问题。实验表明,该方法易于实现且具有较高的精确性、可行性和有效性。