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Journal articles on the topic 'Ontology design'

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1

Vasconcellos, Wander dos Santos, Kate Revoredo, and Fernanda Baião. "How Can Ontology Design Patterns Help Ontology Refinement?" Learning and Nonlinear Models 12, no. 1 (2014): 4–16. http://dx.doi.org/10.21528/lnlm-vol12-no1-art1.

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WANG, YAPING, GUIHUA HAN, JIANGHUA GE, JINGRUI QI, and JIANYUAN XU. "RESEARCH ON DESIGN METHOD OF DEMAND-DRIVEN PRODUCT CONFIGURATION FOR MASS CUSTOMIZATION." Journal of Advanced Manufacturing Systems 10, no. 01 (June 2011): 117–25. http://dx.doi.org/10.1142/s0219686711002053.

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This paper proposed demand-driven personalized product configuration design method. A variety of customer orders were clustered and fuzzy transformed; using ontology's feature to establish customer demand ontology model; in order to enable the product family to meet the dynamic demand of customers, established mapping relationship of customer demands and product family; using ontology to express product family model, achieved mapping of customer needs ontology and product family ontology, and improved efficiency of product configuration. Finally, we take planetary reducer as an example to demonstrate the feasibility of the method.
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Zhang, Kun, Yoshifumi Nishida, Koji Kitamura, and Yoshiki Mikami. "1026 Desing ontology for kids design database." Injury Prevention 22, Suppl 2 (September 2016): A366.1—A366. http://dx.doi.org/10.1136/injuryprev-2016-042156.1026.

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Scharffe, François, Ondřej Zamazal, and Dieter Fensel. "Ontology alignment design patterns." Knowledge and Information Systems 40, no. 1 (April 26, 2013): 1–28. http://dx.doi.org/10.1007/s10115-013-0633-y.

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Bennett, Mike. "Ontology design patterns and semantic abstractions in ontology integration." Applied Ontology 12, no. 3-4 (November 2, 2017): 341–49. http://dx.doi.org/10.3233/ao-170187.

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Song, Hua Zhu, Khamis Abdul Latif Khamis, and Xuan Zhu Song. "Ontology Design in Visual Stock Information System." Advanced Materials Research 225-226 (April 2011): 771–75. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.771.

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The technology of visualization should be merged with semantic technology for abstracting and describing information from the processed DataStream, transaction data and high dimension data in the stock market. This paper proposed the ontology design in visual Stock Information System (VSIS) which combined domain information with function requirements. Firstly, use case diagram and ontology design principles of VSIS were given. Then, according to different information sources and learning theory, learning procedure, validation procedure and their interactions comprised the ontology learning cycle, whose result is VSIS top ontology pools. Next, the ontology in VSIS was defined, whose top ontology covered stock ontology, agent ontology, enquire ontology, visualization ontology, interface ontology, DB operation ontology and error processing ontology. Finally, the defined ontology was validated by Protégé.
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Mata, Ivan, Georges Fadel, and Gregory Mocko. "Toward automating affordance-based design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 29, no. 3 (July 28, 2015): 297–305. http://dx.doi.org/10.1017/s0890060415000256.

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AbstractThe objective of this research is to develop a computational representation of knowledge associated with affordance-based design (ABD). The ABD ontology formalizes the entities, properties, and relationships within the domains of ABD. The ontology enables designers to describe the affordances of existing products and specify the intended affordances of future products in line with ABD. The ontology consists of 14 concepts and 5 relationships. The ontology is developed using Protégé 4.3 and DL-query to query and reason with the ontology. The ontology is demonstrated using a consumer vacuum cleaner. The formal ontology serves as the basis for developing computer support for ABD applications. When implemented, these design tools will help designers manage the affordances of artifacts being designed, specifying the interacting entities of every affordance when a three-dimensional model of the artifact is available. Further, these software tools could be used to support ABD methods.
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Blomqvist, Eva, Pascal Hitzler, Krzysztof Janowicz, Adila Krisnadhi, Tom Narock, and Monika Solanki. "Considerations regarding Ontology Design Patterns." Semantic Web 7, no. 1 (November 10, 2015): 1–7. http://dx.doi.org/10.3233/sw-150202.

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Li, Guan Yu, Yan Zhao, and Hai Yan Li. "Imprecise Ontology Merging Framework Design." Applied Mechanics and Materials 135-136 (October 2011): 578–84. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.578.

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Precision is selected unwillingly by human being when dealing with imprecise objects because of the limitation of human cognitive ability, which deviates from the substance of the processed object when it gets the feasible way of solution. Nowadays, in terms of the research in the Ontology and the Semantic Web, the time for the transformation from the “precise phase” to the “imprecise phase” is ripe. The interoperability among ontologies is seriously blocked by the heterogeneity of ontologies constructed under distributed environment. In this case, Ontology merging in the same domain is the most effective method to solve ontology heterogeneity. Firstly, the improved fuzziness and the R-improved roughness are respectively defined and verified as the more efficient measure way for the fuzziness and roughness. Secondly, a composite appraisal method of fuzzy-rough relevancy in combination of the fuzzy set theory and the rough set theory is proposed, which can serve as the basis of the inquiry and reasoning of the imprecise ontology, the transformation reference of the fuzzy roughness set or the rough fuzziness set. Lastly, by employing semantic bridge generator and conflict processor, a novel multiple-mapping-based imprecise ontology merging framework is proposed. The example verification reveals that both the imprecise ontology merging efficiency can be improved and the merging source imprecise ontologies into object imprecise ontology can be done automatically under the semantic web environment.
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Křemen, P., and Z. Kouba. "Ontology-Driven Information System Design." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42, no. 3 (May 2012): 334–44. http://dx.doi.org/10.1109/tsmcc.2011.2163934.

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Green, Stephen, Darren Southee, and John Boult. "Towards a Design Process Ontology." Design Journal 17, no. 4 (December 2014): 515–37. http://dx.doi.org/10.2752/175630614x14056185480032.

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Keet, C. Maria. "Dependencies between ontology design parameters." International Journal of Metadata, Semantics and Ontologies 5, no. 4 (2010): 265. http://dx.doi.org/10.1504/ijmso.2010.035550.

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Park, Ok nam. "Opening Ontology Design: A Study of the Implications of Knowledge Organization for Ontology Design." KNOWLEDGE ORGANIZATION 35, no. 4 (2008): 209–21. http://dx.doi.org/10.5771/0943-7444-2008-4-209.

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Shi, Xin. "Construction of Design Process Ontology Database Based on Process Ontology." Applied Mechanics and Materials 263-266 (December 2012): 3352–56. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.3352.

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Based on product design process knowledge reuse, according to the characteristics of ontology knowledge representation, process ontology knowledge representation method is offered. The paper extracts the category of design process, defines and describes the attribute and relationship of these categories. Then, the design process ontology database based on process ontology is constructed. As a result, it supports to achieve the sharing and reusing of design process knowledge.
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Lubani, Mohamed, Shahrul Azman Mohd Noah, and Rohana Mahmud. "Ontology population: Approaches and design aspects." Journal of Information Science 45, no. 4 (September 25, 2018): 502–15. http://dx.doi.org/10.1177/0165551518801819.

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Ontologies provide a means to store knowledge in a machine-readable format. Ontology population is the task of updating an ontology with new facts from an input knowledge resource. These facts are represented in a structured format and integrated thereafter into the existing knowledge in the ontology. Textual resources are the dominant online knowledge resources that contain a large number of facts expressed either explicitly or implicitly. Hence, the automatic processing of the extensive knowledge available in these resources has recently gained increasing interest. This study discusses the major components of ontology population process and the different design aspects to be considered when building ontology population systems. In addition, this research explains the different approaches and techniques adopted to carry out the task of ontology population. The possible choices of the design aspects and the related issues are identified and analysed using a set of representative ontology population systems. This study concludes by describing the remaining open issues that should be further explored in ontology population.
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von Rosing, Mark, and Wim Laurier. "An Introduction to the Business Ontology." International Journal of Conceptual Structures and Smart Applications 3, no. 1 (January 2015): 20–41. http://dx.doi.org/10.4018/ijcssa.2015010102.

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Based on the long-standing work of the Global University Alliance and its members, ontology is introduced for the business domain. This ‘business ontology' incorporates all the constructs that can be found in the most popular business standards and frameworks. The business ontology's research and development journey is detailed; in terms of the how the research and findings came about, including the underlying academic design science that is informed by practitioners' industrial experiences. It explains the value of ontology, from which the need for the business ontology can be justified and gives it presence in business practice. The paper concludes with a discussion on the ontology's present status and future potential.
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Kim, Kyoung-Yun, Hyungjeong Yang, and David G. Manley. "Assembly Design Ontology for Service-Oriented Design Collaboration." Computer-Aided Design and Applications 3, no. 5 (January 2006): 603–13. http://dx.doi.org/10.1080/16864360.2006.10738414.

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18

Lopez, M. F., A. Gomez-Perez, J. P. Sierra, and A. P. Sierra. "Building a chemical ontology using Methontology and the Ontology Design Environment." IEEE Intelligent Systems 14, no. 1 (January 1999): 37–46. http://dx.doi.org/10.1109/5254.747904.

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19

Zhang, Mei, Yan Yan, R. H. Wang, and Jia Hao. "Ontology-Based Knowledge Management for Vehicle Design." Materials Science Forum 626-627 (August 2009): 639–44. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.639.

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To utilize vehicle design knowledge reasonably and effectively, ontology is introduced in this paper and vehicle design domain ontology is constructed within three steps which are: extracting the significant terminologies and concepts in the field, establishing ontology framework, constructing vehicle design domain ontological relation tree combining development tool. According to the method, vehicle design ontological relation tree is built and evaluated through descriptive evaluation and verifiable evaluation. The results are applied in knowledge representation which adopts SVPO (Subject + Verb + Parameter + Object) mode and knowledge retrieval, the effectiveness of ontology is verified in our system. Finally the paper concluded a concurrent method of ontology construction.
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Lee, In-K., and Soon-H. Kwon. "Design of Ontology-based Intelligent Agents." Journal of Korean Institute of Intelligent Systems 18, no. 3 (June 25, 2008): 347–53. http://dx.doi.org/10.5391/jkiis.2008.18.3.347.

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21

CAO, Dongxing. "Port-based Ontology Conceptual Design Theory." Journal of Mechanical Engineering 46, no. 17 (2010): 123. http://dx.doi.org/10.3901/jme.2010.17.123.

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Khruahong, Sanya, Xiaoying Kong, and Doan Hoang. "Ontology Design for Thailand Travel Industry." International Journal of Knowledge Engineering 1, no. 3 (2015): 191–96. http://dx.doi.org/10.18178/ijke.2015.1.3.033.

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23

AlShehri, Majdah, and Azeddin Chikh. "Ontology Learning Design toward Supporting Designer." International Journal of Computer Applications 74, no. 4 (July 26, 2013): 45–50. http://dx.doi.org/10.5120/12877-9957.

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24

Yu, Juan, Yan Zhong Dang, and Ming Zheng Wang. "On Design of Ontology Management Systems." Advanced Materials Research 403-408 (November 2011): 2396–99. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2396.

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An ontology management system (OMS) is a software system which manages ontologies through their lifecycle. It simplifies ontologies building and applications by providing a mechanism for querying ontologies and an easy-to-use programming interface to ontologies and instances. OMSs are powerful tools to create ontologies and extend their applications and scope. This paper explains the basic design principles of an OMS and designs a general framework of OMSs. It devotes to promoting systematically research and development of OMSs.
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25

Gero, John S., and Udo Kannengiesser. "An ontology of situated design teams." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21, no. 3 (August 2007): 295–308. http://dx.doi.org/10.1017/s0890060407000297.

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AbstractThis paper presents an ontological framework for situated design teams in which the team is both the subject and the object of designing. Team designing is modeled using the set of processes provided by the situated function–behavior–structure framework. This is a formal basis for understanding the drivers for change in the product to be designed and in the design team. We specifically focus on changes in a team's structure that emerge from interactions among individual team members and subteams.
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Bravo Contreras, Maricela Claudia, Luis Fernando Hoyos Reyes, and José Alejandro Reyes Ortiz. "Methodology for ontology design and construction." Contaduría y Administración 64, no. 4 (March 19, 2019): 134. http://dx.doi.org/10.22201/fca.24488410e.2020.2368.

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27

Holsapple, Clyde W., and K. D. Joshi. "A collaborative approach to ontology design." Communications of the ACM 45, no. 2 (February 2002): 42–47. http://dx.doi.org/10.1145/503124.503147.

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28

Lindley, Joseph, Haider Ali Akmal, and Paul Coulton. "Design Research and Object-Oriented Ontology." Open Philosophy 3, no. 1 (January 24, 2020): 11–41. http://dx.doi.org/10.1515/opphil-2020-0002.

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AbstractIn this paper we recount several research projects conducted at ImaginationLancaster (http://imagination.lancs.ac.uk) a Design-led research laboratory, all of which consider Object-Oriented Ontology (OOO). The role OOO plays in these projects is varied: as a generative mechanism contributing to ideation; as a framework for analysis; and as a constituent in developing new design theory. Each project’s focus is quite unique—an app, a board game, a set of Tarot cards, a kettle and a living room—however they are all concerned with developing new understandings relating to the ubiquitous, networked, ‘smart’ technologies which are often referred to as the Internet of Things (IoT). Through our reflexive account of these research projects the aim of this paper is to provide insights into, and promote new discussion about, the relevance and scope for OOO in socio-technical Design Research, and beyond.
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Garzas, J., and M. Piattini. "An Ontology for Microarchitectural Design Knowledge." IEEE Software 22, no. 2 (March 2005): 28–33. http://dx.doi.org/10.1109/ms.2005.26.

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NOMAGUCHI, Yutaka, and Kikuo FUJITA. "2404 Design Methodology and Ontology Building." Proceedings of Design & Systems Conference 2006.16 (2006): 232–35. http://dx.doi.org/10.1299/jsmedsd.2006.16.232.

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Silva-López, Rafaela Blanca, Mónica Silva-López, Maricela Bravo, Iris Iddaly Méndez-Gurrola, and Victor Germán Sánchez Arias. "GODeM: A Graphical Ontology Design Methodology." Research in Computing Science 84, no. 1 (December 31, 2014): 17–28. http://dx.doi.org/10.13053/rcs-84-1-2.

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Tang, Guo Xing, Hun Guo, and W. D. Jin. "An Ontology-Based Design Knowledge Model." Key Engineering Materials 426-427 (January 2010): 697–700. http://dx.doi.org/10.4028/www.scientific.net/kem.426-427.697.

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In this paper, we investigated the knowledge modeling and proposed an ontology-based representation approach 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.
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Wei, Sun, Ma Qin-yi, and Gao Tian-yi. "An Ontology-Based Manufacturing Design System." Information Technology Journal 8, no. 5 (June 15, 2009): 643–56. http://dx.doi.org/10.3923/itj.2009.643.656.

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Jinxin Lin, Mark S. Fox, and Taner Bilgic. "A Requirement Ontology for Engineering Design." Concurrent Engineering 4, no. 3 (September 1996): 279–91. http://dx.doi.org/10.1177/1063293x9600400307.

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Liu, Yong, Xiaoling Zheng, Feng Tang, and Xiaofei Chen. "Ontology design with a granular approach." Expert Systems with Applications 41, no. 10 (August 2014): 4867–77. http://dx.doi.org/10.1016/j.eswa.2014.02.019.

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36

Fernández, Norberto, Damaris Fuentes, Luis Sánchez, and Jesús A. Fisteus. "The NEWS ontology: Design and applications." Expert Systems with Applications 37, no. 12 (December 2010): 8694–704. http://dx.doi.org/10.1016/j.eswa.2010.06.055.

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37

LI, ZHANJUN, and KARTHIK RAMANI. "Ontology-based design information extraction and retrieval." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21, no. 2 (March 19, 2007): 137–54. http://dx.doi.org/10.1017/s0890060407070199.

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Because of the increasing complexity of products and the design process, as well as the popularity of computer-aided documentation tools, the number of electronic and textual design documents being generated has exploded. The availability of such extensive document resources has created new challenges and opportunities for research. These include improving design information retrieval to achieve a more coherent environment for design exploration, learning, and reuse. One critical issue is related to the construction of a structured representation for indexing design documents that record engineers' ideas and reasoning processes for a specific design. This representation should explicitly and accurately capture the important design concepts as well as the relationships between these concepts so that engineers can locate their documents of interest with less effort. For design information retrieval, we propose to use shallow natural language processing and domain-specific design ontology to automatically construct a structured and semantics-based representation from unstructured design documents. The design concepts and relationships of the representation are recognized from the document based on the identified linguistic patterns. The recognized concepts and relationships are joined to form a concept graph. The integration of these concept graphs builds an application-specific design ontology, which can be seen as the structured representation of the content of the corporate document repository, as well as an automatically populated knowledge base from previous designs. To improve the performance of design information retrieval, we have developed ontology-based query processing, where users' requests are interpreted based on their domain-specific meanings. Our approach contrasts with the traditionally used keyword-based search. An experiment to test the retrieval performance is conducted by using the design documents from a product design scenario. The results demonstrate that our method outperforms the keyword-based search techniques. This research contributes to the development and use of engineering ontology for design information retrieval.
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Li, Jia, Yun Bin Yang, and Li Fan Wei. "Ontology-Based Knowledge Representation for Mechanical Products." Advanced Materials Research 605-607 (December 2012): 365–70. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.365.

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Knowledge Based Engineering (KBE) helps sharing and reusing knowledge in modern mechanical design field. As a core part of KBE, various methods of knowledge representation were studied. In order to reuse the mechanical design knowledge, the methodology of ontology-based knowledge representation was discussed. First, the concepts, formal description, specialties and languages of ontology were described. Then, three categories of ontology in the field of mechanical design, general ontology, domain ontology and product ontology, were discussed. The product ontology was analyzed by the configuration design method. Finally, an example of ontology-based knowledge representation for mechanical products was studied. The work about ontology-based knowledge representation methodology may support the application of KBE in mechanical design field.
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Ahmed, Saeema, Sanghee Kim, and Ken M. Wallace. "A Methodology for Creating Ontologies for Engineering Design." Journal of Computing and Information Science in Engineering 7, no. 2 (October 26, 2006): 132–40. http://dx.doi.org/10.1115/1.2720879.

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This paper describes a six-stage methodology for developing ontologies for engineering design, together with the research methods and evaluation of each stage. The methodology focuses upon understanding a user’s domain models through empirical research. A case study of an ontology for searching, indexing, and retrieving engineering knowledge is described. The root concepts of the ontology were elicited from engineering designers. Relationships between concepts are extracted as the ontology is populated. The contribution of this research is a methodology to allow researchers and industry to create ontologies for their particular purpose and a thesaurus for the terms within the ontology.
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Cahyani, Denis Eka, and Ito Wasito. "Automatic Ontology Construction Using Text Corpora and Ontology Design Patterns (ODPs) in Alzheimer’s Disease." Jurnal Ilmu Komputer dan Informasi 10, no. 2 (June 30, 2017): 59. http://dx.doi.org/10.21609/jiki.v10i2.374.

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An ontology is defined as an explicit specification of a conceptualization, which is an important tool for modeling, sharing and reuse of domain knowledge. However, ontology construction by hand is a complex and a time consuming task. This research presents a fully automatic method to build bilingual domain ontology from text corpora and ontology design patterns (ODPs) in Alzheimer’s disease. This method combines two approaches: ontology learning from texts and matching with ODPs. It consists of six steps: (i) Term & relation extraction (ii) Matching with Alzheimer glossary (iii) Matching with ontology design patterns (iv) Score computation similarity term & relation with ODPs (v) Ontology building (vi) Ontology evaluation. The result of ontology composed of 381 terms and 184 relations with 200 new terms and 42 new relations were added. Fully automatic ontology construction has higher complexity, shorter time and reduces role of the expert knowledge to evaluate ontology than manual ontology construction. This proposed method is sufficiently flexible to be applied to other domains.
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Anticoli, Linda, and Elio Toppano. "How Culture May Influence Ontology Co-Design." International Journal of Information Technology and Web Engineering 6, no. 2 (April 2011): 1–17. http://dx.doi.org/10.4018/jitwe.2011040101.

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This article addresses the issue of cultural influence in ontology design and reuse. The main assumption is that an ontology is not only a socio-technical artefact but also a cultural artefact. It contains embedded assumptions, core values, points of view, beliefs, thought patterns, etc. Based on results already found in several design fields the authors formulate some preliminary hypotheses about the possible relationships existing between culture and features of design process and produced ontology. A critical and qualitative analysis of six collaborative design systems has been performed to test some of the hypotheses, confirming some of the findings. The authors argue that a “culture aware” attitude may be of great importance for supporting the processes of cross cultural collaborative ontology design and the internalization and localization of these kinds of artefacts.
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Ming, Zhenjun, Yan Yan, Guoxin Wang, Jitesh H. Panchal, Chung-Hyun Goh, Janet K. Allen, and Farrokh Mistree. "Ontology-based executable design decision template representation and reuse." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 30, no. 4 (October 4, 2016): 390–405. http://dx.doi.org/10.1017/s0890060416000378.

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AbstractIn decision-based design, the principal role of a designer is to make decisions. Decision support is crucial to augment this role. In this paper, we present an ontology that provides decision support from both the “construct” and the “information” perspectives that address the gap that existing research focus on these two perspectives separately and cannot provide effective decision support. The decision support construct in the ontology is the compromise decision support problem (cDSP) that is used to make multiobjective design decisions. The information for decision making is archived as cDSP templates and represented using frame-based ontology for facilitating reuse, consistency maintaining, and rapid execution. In order to facilitate designers’ effective reuse of the populated cDSP templates ontology instances, we identified three types of modification that can be made when design consideration evolves. In our earlier work, part of the utilization (consistency checking) of the ontology has been demonstrated through a thin-walled pressure vessel redesign example. In this paper, we comprehensively present the ontology utilization including consistency checking, trade-off analysis, and design space visualization based on the pressure vessel example.
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Mashwani, S. R., and S. Khusro. "The Design and Development of a Semantic File System Ontology." Engineering, Technology & Applied Science Research 8, no. 2 (April 19, 2018): 2827–33. http://dx.doi.org/10.48084/etasr.1898.

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Semantic File System (SFS) is the vision for the future of file systems where information is given with explicit meaning to be processed by machines automatically and consumed by the users easily. SFSs extend traditional file systems to organize and retrieve information according to their semantics, intent and relationships with other resources rather than their physical locations. Ontology-based file system is a step to dissolve the borders between semantic web and semantic desktop to make the desktop part of a single giant web. Unfortunately, to the best of the authors’ current knowledge, so far, no effort has been exercised to develop an ontology for SFSs. This work contributes a SFS ontology, which extends NEPOMUK information element ontology framework into the domain of SFSs. The proposed SFS ontology is freely available with full technical definitions of terms and complete class hierarchy to be used for any purpose in information technology (IT). In addition, as a proof-of-concept implementation, we deploy the proposed ontology in the 360ᵒ SFS. Finally, to get most of the benefits of the ontology, this paper also presents a semantics-aware file manager.
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Espinoza, Angelina, Ernesto Del-Moral, Alfonso Martínez-Martínez, and Nour Alí. "A validation & verification driven ontology: An iterative process." Applied Ontology 16, no. 3 (July 21, 2021): 297–337. http://dx.doi.org/10.3233/ao-210251.

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Designing an ontology that meets the needs of end-users, e.g., a medical team, is critical to support the reasoning with data. Therefore, an ontology design should be driven by the constant and efficient validation of end-users needs. However, there is not an existing standard process in knowledge engineering that guides the ontology design with the required quality. There are several ontology design processes, which range from iterative to sequential, but they fail to ensure the practical application of an ontology and to quantitatively validate end-user requirements through the evolution of an ontology. In this paper, an ontology design process is proposed, which is driven by end-user requirements, defined as Competency Questions (CQs). The process is called CQ-Driven Ontology DEsign Process (CODEP) and it includes activities that validate and verify the incremental design of an ontology through metrics based on defined CQs. CODEP has also been applied in the design and development of an ontology in the context of a Mexican Hospital for supporting Neurologist specialists. The specialists were involved, during the application of CODEP, in collecting quality measurements and validating the ontology increments. This application can demonstrate the feasibility of CODEP to deliver ontologies with similar requirements in other contexts.
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45

Zeng, Qing Liang, Zhi Hai Liu, Li Rong Wan, and Yong Hua Zhao. "Research on Workflow Management of Multi-Disciplinary Collaborative Design Based on Ontology." Key Engineering Materials 419-420 (October 2009): 757–60. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.757.

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In this paper, the mechanism of workflow management based on ontology of multi disciplinary collaborative design is studied. Based on the integrative research of key technologies of semantic technology and semantic retrieval and workflow management, an ontology-based workflow framework of multi-disciplinary collaborative design is put forward. Models of workflow-related elements on different levels were built up according to subjects related in collaborative design. An ontology-based workflow model library of multi-disciplinary collaborative design is set up by using RDF. The currently popular ontology retrieval strategy is analyzed, and an ontology model search engine in workflow of multidisciplinary collaborative design is set up by combining the keywords-based with ontology-based semantic search.
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46

Jakkilinki, R., N. Sharda, and I. Ahmad. "MUDPY ontology: a tool for multimedia project planning, design and development." Journal of Enterprise Information Management 19, no. 2 (March 1, 2006): 165–74. http://dx.doi.org/10.1108/17410390610645067.

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PurposeThis paper seeks to describe the process used to develop the multimedia design and planning pyramid (MUDPY) ontology, and the role played by the MUDPY ontology as a planning, design and development tool in multimedia projects.Design/methodology/approachThe MUDPY model was implemented for the semantic web by developing an ontology for it. This ontology facilitates defining the concepts existing in that domain, their attributes and the relationships between them.FindingsThe MUDPY ontology can guide developers through the various phases of a multimedia project in a systematic fashion by allowing them to create a project proposal, specify the functional requirements, decide on the navigational structure and create a storyboard, and thus create high‐quality projects.Research limitations/implicationsThe current system is a prototype. This MUDPY ontology can be extended by adding more classes in order to increase its functionality; for example, one can develop special plug‐in widgets to generate project reports required during multimedia project planning and design.Practical implicationsBy using the MUDPY ontology, developers can follow a systematic process for project development, and better manage the complexity of multimedia projects.Originality/valueThe paper introduces the MUDPY model and its ontology, and shows a multimedia author the pathway to manage a multitude of concepts and assets required in a multimedia project.
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Harjito, Bambang, Denis Eka Cahyani, and Afrizal Doewes. "An Automatic Approach for Bilingual Tuberculosis Ontology Based on Ontology Design Patterns (ODPs)." TELKOMNIKA (Telecommunication Computing Electronics and Control) 16, no. 1 (February 1, 2018): 282. http://dx.doi.org/10.12928/telkomnika.v16i1.6587.

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Lebedev, Sergey, and Michail Panteleyev. "Ontology-Driven Situation Assessment System Design and Development in IoT Domains." International Journal of Embedded and Real-Time Communication Systems 8, no. 1 (January 2017): 1–17. http://dx.doi.org/10.4018/ijertcs.2017010101.

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An ontology-driven approach to software design and development of situation assessment systems (SAS) for IoT applications is considered. As SAS is used to build the situational model for the external environment, it highly depends on the operational domain. To simplify the transition from the domain description to SAS dataflow process the ontology-driven approach is proposed. The main idea of the approach is to explicitly formalize SAS dataflow process in an ontological form. For this purpose, a domain-independent SAS ontology is proposed that allows automation of the dataflow process design. The dataflow process ontology is used to automate development and runtime stages of SAS lifecycle. The proposed ontology is included into the proposed instrument set. The set can be used to build SAS systems for different domains described with OWL ontology. The set is evaluated on a traffic control scenario.
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Li, Li Li, Jiu Hua Li, and Kai He. "The Gene Ontology for Product Image Design." Applied Mechanics and Materials 319 (May 2013): 257–62. http://dx.doi.org/10.4028/www.scientific.net/amm.319.257.

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Inspired by DNA , the genetic gene in biosphere, this paper has systematically analysed the importance of product image design result from the spiritual elements and visual elements of product image. And combined with successful design case, the advantageous influence on product image design by gene elements is presented in depth. The theoretic basis of product design style based on the gene elements of product has been established, which makes the design process more effective and more systematical. Meanwhile, it makes the gene elements of product image design more realizable, through analyzing the composition of product gene elements.
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Фазылзянова, Г. И., T. Yu Sokolova,, N. A. Likht, D. V. Ivanova, and T. N. Petrenko. "Creative design ontology in a digital society." Ekonomicheskie i sotsial’no-gumanitarnye issledovaniya, no. 2(26) (June 2020): 130–34. http://dx.doi.org/10.24151/2409-1073-2020-2-130-134.

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