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1 – 10 of over 4000O.O. UGWU, C.J. ANUMBA and A. THORPE
Domain ontologies facilitate sharing and re‐use of data and knowledge between distributed collaborating systems. A major problem in the design and application of intelligent…
Abstract
Domain ontologies facilitate sharing and re‐use of data and knowledge between distributed collaborating systems. A major problem in the design and application of intelligent systems is to capture and understand: the data and information model that describes the domain; the various levels of knowledge associated with problem solving; and the patterns of interaction, information and data flow in the problem solving space. This paper reports the development of an ontology for agent‐based collaborative design of portal structures, using knowledge acquisition techniques and tools. It illustrates the application of the ontology in the development of a prototype multi‐agent systems. The study shows that a common ontology facilitates interaction and negotiation between agents and other distributed systems. The paper discusses the findings from the knowledge acquisition, their implications in the design and implementation of multi‐agent systems, and gives recommendations on developing agent‐based systems for collaborative design and decision‐support in the construction sector.
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Sidi Mohamed Benslimane, Mimoun Malki and Djelloul Bouchiha
Web applications are subject to continuous changes and rapid evolution triggered by increasing competition, especially in commercial domains such as electronic commerce…
Abstract
Purpose
Web applications are subject to continuous changes and rapid evolution triggered by increasing competition, especially in commercial domains such as electronic commerce. Unfortunately, usually they are implemented without producing any useful documentation for subsequent maintenance and evolution. Thereof, the maintenance of such systems becomes a challenging problem as the complexity of the web application grows. Reverse engineering has been heralded as one of the most promising technologies to support effective web application maintenance. This paper aims to present a reverse engineering approach that helps understanding existing undocumented web applications to be maintained or evolved.
Design/methodology/approach
The proposed approach provides reverse engineering rules to generate a conceptual schema from a given domain ontology by using a set of transformation rules. The reverse engineering process consists of four phases: extracting useful information; identifying a set of ontological constructs representing the concepts of interest; enriching the identified set by additional constructs; and finally deriving a conceptual schema.
Findings
The advantage of using ontology for conceptual data modeling is the reusability of domain knowledge. As a result, the conceptual data model will be made faster, easier and with fewer errors than creating it in usual way. Designers can use the extracted conceptual schema to gain a better understanding of web applications and to assist in their maintenance.
Originality/value
The strong point of this approach is that it relies on a very rich semantic reference that is domain ontology. However, it is not possible to make a straightforward transformation of all elements from a domain ontology into a conceptual data model because ontology is semantically richer than data conceptual models.
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Joselaine Valaski, Sheila Reinehr and Andreia Malucelli
The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a…
Abstract
Purpose
The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area.
Design/methodology/approach
An ontology for recommending learning material was integrated in the organizational learning environment based on ontology. An experiment was performed with 15 experts and 84 learners. Experts and learners were asked to classify 30 learning material related to Software Engineering area. The results obtained from experts and learners were compared with the ontology results.
Findings
Among 30 learning materials evaluated, 24 learning materials got closer to the expert classification using the ontology than using the learners’ manual classification. The learners had difficulties in correctly classifying the learning materials according to the knowledge area applied.
Originality/value
In an autonomous collaborative environment without a tutor responsible for organizing the learning materials shared by collaborators, an ontology may be an auxiliary mechanism to support automatic learning material classification. The proposed ontology uses recommendations given by the collaborators to get the correct knowledge area classification. The correct classification may support retrieval of appropriate learning materials according to the learners’ needs.
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Denny Vrandečić, Sofia Pinto, Christoph Tempich and York Sure
Aims to present the ontology engineering methodology DILIGENT, a methodology focussing on the evolution of ontologies instead of the initial design, thus recognizing that…
Abstract
Purpose
Aims to present the ontology engineering methodology DILIGENT, a methodology focussing on the evolution of ontologies instead of the initial design, thus recognizing that knowledge is a tangible and moving target.
Design/methodology/approach
First describes the methodology as a whole, then detailing one of the five main steps of DILIGENT. The second part describes case studies, either already performed or planned, and what we learned (or expect to learn) from them.
Findings
With the case studies it was discovered the strengths and weaknesses of DILIGENT. During the evolution of ontologies, arguments need to be exchanged about the suggested changes. Identifies those kind of arguments which work best for the discussion of ontology changes.
Research implications
DILIGENT recognizes ontology engineering methodologies like OnToKnowledge or Methontology as proven useful for the initial design, but expands them with its strong focus on the user‐centric further development of the ontology and the provided integration of automatic agents in the process of ontology evolution.
Practical implications
With DILIGENT the experience distilled from a number of case studies and offers the knowledge manager a methodology to work in an ever‐changing environment.
Originality/value
DILIGENT is the first methodology to put focus not on the initial development of the ontology, but on the user and his usage of the ontology, and on the changes introduced by the user. We take the user's own view seriously and enable feedback towards the evolution of the ontology, stressing the ontology's role as a shared conceptualisation.
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Abla Chaouni Benabdellah, Kamar Zekhnini, Surajit Bag, Shivam Gupta and Ana Beatriz Lopes de Sousa Jabbour
This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different…
Abstract
Purpose
This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different design for X techniques.
Design/methodology/approach
This study follows a thematic literature analysis to identify the key design concepts needed to assess environmental, service, safety, manufacture and assembly, supply chain and quality concerns in developing a collaborative PDP.
Findings
The proposed model provides a guide for methodology, engineering and ontology evaluation metrics (verification, assessment and validation). The findings benefit both practitioners and managers because they address the key knowledge taxonomy needed to assist them in storing information, promoting teamwork and making decisions in a collaborative PDP while incorporating various design for X approaches and product life cycles.
Originality/value
This study introduces a novel knowledge-based collaborative ontological research model, which is specifically designed to tackle the challenges of developing collaborative products in the contemporary landscape. The model presents a significant and valuable contribution to the field by introducing an ontological approach for acquiring, representing and leveraging knowledge in a computer-interpretable format to support the design of collaborative products. In addition, it provides a comprehensive guide for evaluating the effectiveness and efficacy of the ontology developed.
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Xiaoming Zhang, Kai Li, Chongchong Zhao and Dongyu Pan
With the increasing spread of ontologies in various domains, units have gradually become an essential part of ontologies and units ontologies have been developed to offer a better…
Abstract
Purpose
With the increasing spread of ontologies in various domains, units have gradually become an essential part of ontologies and units ontologies have been developed to offer a better expression ability for the practical usage. From the perspectives of architecture, comparison and reuse, the purpose of this paper is to provide a comprehensive survey on four mainstream units ontologies: quantity-unit-dimension-type, quantities, units, dimensions and values, ontology of units of measure and units ontology (UO) of the open biomedical ontologies, in order to address well the state of the art and the reuse strategies of the UO.
Design/methodology/approach
An architecture of units ontologies is presented, in which the relations between key factors (i.e. units of measure, quantity and dimension) are discussed. The criteria for comparing units ontologies are developed from the perspectives of organizational structure, pattern design and application scenario. Then, the authors compare four typical units ontologies based on the proposed comparison criteria. Furthermore, how to reuse these units ontologies is discussed in materials science domain by utilizing two reuse strategies of partial reference and complete reference.
Findings
Units ontologies have attracted high attention in the scientific domain. Based on the comparison of four popular units ontologies, this paper finds that different units ontologies have different design features from the perspectives of basis structure, units conversion and axioms design; a UO is better to be applied to the application areas that satisfy its design features; and many challenges remain to be done in the future research of the UO.
Originality/value
This paper makes an extensive review on units ontologies, by defining the comparison criteria and discussing the reuse strategies in the materials domain. Based on this investigation, guidelines are summarized for the selection and reuse of units ontologies.
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Ahmet Coşkunçay and Onur Demirörs
From knowledge management point of view, business process models and ontologies are two essential knowledge artifacts for organizations that consume similar information sources…
Abstract
Purpose
From knowledge management point of view, business process models and ontologies are two essential knowledge artifacts for organizations that consume similar information sources. In this study, the PROMPTUM method for integrated process modeling and ontology development that adheres to well-established practices is presented. The method is intended to guide practitioners who develop both ontologies and business process models in the same or similar domains.
Design/methodology/approach
The method is supported by a recently developed toolset, which supports the modeling of relations between the ontologies and the labels within the process model collections. This study introduces the method and its companion toolset. An explanatory study, that includes two case studies, is designed and conducted to reveal and validate the benefits of using the method. Then, a follow-up semi-structured interview identifies the perceived benefits of the method.
Findings
Application of the method revealed several benefits including the improvements observed in the consistency and completeness of the process models and ontologies. The method is bringing the best practices in two domains together and guiding the use of labels within process model collections in ontology development and ontology resources in business process modeling.
Originality/value
The proposed method with its tool support is a pioneer in enabling to manage the labels and terms within the labels in process model collections consistently with ontology resources. Establishing these relations enables the definition and management of process model elements as resources in domain ontologies. Once the PROMPTUM method is utilized, a related resource is managed as a single resource representing the same real-world object in both artifacts. An explanatory study has shown that improvement in consistency and completeness of process models and ontologies is possible with integrated process modeling and ontology development.
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Prashant Kumar Sinha, Biswanath Dutta and Udaya Varadarajan
The current work provides a framework for the ranking of ontology development methodologies (ODMs).
Abstract
Purpose
The current work provides a framework for the ranking of ontology development methodologies (ODMs).
Design/methodology/approach
The framework is a step-by-step approach reinforced by an array of ranking features and a quantitative tool, weighted decision matrix. An extensive literature investigation revealed a set of aspects that regulate ODMs. The aspects and existing state-of-the-art estimates facilitated in extracting the features. To determine weight to each of the features, an online survey was implemented to secure evidence from the Semantic Web community. To demonstrate the framework, the authors perform a pilot study, where a collection of domain ODMs, reported in 2000–2019, is used.
Findings
State-of-the-art research revealed that ODMs have been accumulated, surveyed and assessed to prescribe the best probable ODM for ontology development. But none of the prevailing studies provide a ranking mechanism for ODMs. The recommended framework overcomes this limitation and gives a systematic and uniform way of ranking the ODMs. The pilot study yielded NeOn as the top-ranked ODM in the recent two decades.
Originality/value
There is no work in the literature that has investigated ranking the ODMs. Hence, this is a first of its kind work in the area of ODM research. The framework supports identifying the topmost ODMs from the literature possessing a substantial amount of features for ontology development. It also enables the selection of the best possible ODM for the ontology development.
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This study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.
Abstract
Purpose
This study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.
Design/methodology/approach
The ontology composes the main framework to categorize data of product life cycle with eco-design mode (PLC-EDM) and automatically infer specialists’ knowledge for data confirmation, eventually assisting the utilizations and generation of strategies toward decision-making
Findings
(i) utilization of a novel model with ontology mode for information reuse cross the different eco-design applications; (ii) generation of a sound platform toward life cycle evaluation; and (iii) implementation of the PLC-EDM model along the product generation process.
Research limitations/implications
It cannot substitute an evaluation tool of life cycle. Certainly, this model does not predict the “target and range” and/or the depiction of the “utility module” that are basic activities in life cycle assessments as characterized through the international organization for standardization regulations.
Practical implications
As portion of this framework, a prototype Web application is presented which is applied to produce, reuse and verify knowledge of product life cycle.
Social implications
By counting upon the ontology, the information conducted by the utilization is certainly semantically represented to promote the data sharing among various participants and tools. Besides, the data can be verified against possible faults by inferring over the ontology. Hence, a feasible way to a popular topic in the domain of eco-design applications extension in the industry.
Originality/value
The goals are: to lean on rigid modeling principles; and to promote the interoperability and diffusion of the ontology toward particular utilization demands.
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Rodolfo Stecher, Claudia Niederée, Wolfgang Nejdl and Paolo Bouquet
The discovery of the “right” ontology or ontology part is a central ingredient for effective ontology re‐use. The purpose of this paper is to present an approach for supporting a…
Abstract
Purpose
The discovery of the “right” ontology or ontology part is a central ingredient for effective ontology re‐use. The purpose of this paper is to present an approach for supporting a form of adaptive re‐use of sub‐ontologies, where the ontologies are deeply integrated beyond pure referencing.
Design/methodology/approach
Starting from an ontology draft which reflects the intended modeling perspective, the ontology engineer can be supported by suggesting similar already existing sub‐ontologies and ways for integrating them with the existing draft ontology. This paper's approach combines syntactic, linguistic, structural and logical methods into an innovative modeling‐perspective aware solution for detecting matchings between concepts from different ontologies. This paper focuses on the discovery and matching phase of this re‐use process.
Findings
Owing to the combination of techniques presented in this general approach, the work described performs in the general case as well as approaches tailored for a specific usage scenario.
Research limitations/implications
The methods used rely on lexical information obtained from the labels of the concepts and properties in the ontologies, which makes this approach appropriate in cases where this information is available. Also, this approach can handle some missing label information.
Practical implications
Ontology engineering tasks can take advantage from the proposed adaptive re‐use approach in order to re‐use existing ontologies or parts of them without introducing inconsistencies in the resulting ontology.
Originality/value
The adaptive re‐use of ontologies by finding and partially re‐using parts of existing ontological resources for building new ontologies is a new idea in the field, and the inclusion of the modeling perspective in the computation of the matches adds a new perspective that could also be exploited by other matching approaches.
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