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Integration of an ontology with IFC for efficient knowledge discovery in the construction domain
Published in Jan Karlshøj, Raimar Scherer, eWork and eBusiness in Architecture, Engineering and Construction, 2018
Z.S. Usman, J.H.M. Tah, F.H. Abanda, C. Nche
The Web Ontology Language (OWL) is the standard language for the ontology layer of the semantic web. It is recommended by the World Wide Web Consortium (W3C) (W3C, 2004). OWL executes great machine interoperability of the contents of the web. It specifies a collection of operators to develop concept definitions and descriptions as well as reasoners to perform consistency checking of the ontology. Ontology developers usually adopt one of OWL and OWL 2 (OWL2 EL, QL and RL) sublanguages which best suits the needs of the application. The expressive power, computational completeness, reasoning capacity and limitations of the OWL sublanguages are amongst the characteristics that are analyzed during selection. The level of expressiveness of the OWL language determines what is represented in the OWL ontology (Pauwels & Terkaj, 2016). The reader is referred to the W3C OWL recommendation document for more details (W3C, 2004). OWL and SWRL together perform extensive semantic reasoning (Chen & Luo, 2016). Thus an ontology provides standard conceptualization and the semantic knowledge reasoning required on the selected domain. In this study, the Photovoltaic (PV) Systems is the selected domain of interest.
Computer Networks
Published in Vivek Kale, Agile Network Businesses, 2017
Ontology is the formal, explicit specification of a shared conceptualization of a particular domain—concepts are the core elements of the conceptualization, corresponding to the entities of the domain being described, and properties and relations are used to describe interconnections between such concepts. Web Ontology Language (OWL) is the standard language for representing knowledge on the Web. This language was designed to be used by applications that need to process the content of information on the Web instead of just presenting information to human users. Using OWL, one can explicitly represent the meaning of terms in vocabularies and the relationships between those terms. The Rule Interchange Format (RIF) is the W3C recommendation that defines a framework to exchange rule-based languages on the Web. Like OWL, RIF defines a set of languages covering various aspects of the rule layer of the Semantic Web.
Ecosystem and platform review for construction information sharing
Published in Symeon E. Christodoulou, Raimar Scherer, eWork and eBusiness in Architecture, Engineering and Construction, 2017
I. Peltomaa, M. Kiviniemi, J. Väre
One of the most used Semantic Web Standard is W3C developed Resource Description Framework (RDF) for representing information in the web. RDF provides means for annotating information in web with semantic markup to enable machine interpretation. For establishing explicit meaning RDF is not enough but ontologies are required. RDF Schema Language (RDFS) extends RDF by defining terms of a knowledge domain and the relationships between them. (Manola & Miller 2004, Pan & Horrocks 2007, Brickley & Guha 2014, Sikos 2015). Web Ontology Language (OWL) is a knowledge representation language supporting the processing of the content of information instead of presenting of it thus enabling machine interpretability capabilities by providing additional vocabulary along with a formal semantics. OWL is especially designed for creating web ontologies with better properties than XML, RDF, and RDFS. OWL has three increasingly-expressive sublanguages: OWL Lite, OWL DL, and OWL Full. (McGuinness & van Harmelen 2004, Sikos 2015)
A design knowledge management model for civil aircraft cabin based on Markov Logic Networks
Published in International Journal of Computer Integrated Manufacturing, 2020
Yahui Wang, Suihuai Yu, Fangmin Cheng, Zhuo Liu, Dengkai Chen, Jianjie Chu, Ning Ma, Yanhao Chen
Design knowledge ontology element of civil aircraft cabin includes user knowledge element and designer knowledge element in the whole design process (Brandt et al. 2008). User design knowledge ontology element refers to user demand, user psychological analysis, user intention and user situation, etc (Wu and Liu 2010; Zhang et al. 2012b). The designer knowledge element includes subjective, fuzzy, descriptive internal tacit knowledge such as design intention, design experience, design technique, design inspiration, and explicit design knowledge such as design specifications, reports and documentation, manuals, regulations, standards and databases, etc (Zhang, Dachao, and Yuchun 2010; Ma and Tian 2015). In order to describe the accurate semantic information represented by design knowledge element, OWL (Web Ontology Language) is used to describe the concrete information of knowledge element about a specific subject (Horrocks, Patel-Schneider, and Frank 2003). OWL uses classes, properties and individuals to describe the formal semantics of objects, such as the description of classes, the relations between classes, properties, the relations between properties and properties constraints (De Vergara, Villagra, and Berrocal 2004; Wang, Yang, and Kong 2003; Matsokis and Kiritsis 2010). In this paper, under the guidance of domain ontology, the design knowledge element ontology is created through semantic label.
Distributed electronic health record based on semantic interoperability using fuzzy ontology: a survey
Published in International Journal of Computers and Applications, 2018
Ebtsam Adel, Shaker El-Sappagh, Sherif Barakat, Mohammed Elmogy
The Web Ontology Language (OWL) is a universal markup language used to exchange and encode ontologies. It is designed for supporting the semantic web. OWL has more skills in expressing semantics and meaning than other markup languages as RDF, XML, and RDF-S. Thus, OWL has the same capabilities of these languages in addition to its ability for representing Web machine interpretable contents. OWL facilitates interoperability while exchanging the healthcare information. It provides the technical framework to reuse the existing ontologies. Also, they provide formal mechanisms for expressing logical equivalences between properties and classes in different ontologies [35]. After studying some of the EHR standards, we found that these standards have some limitations during practical implementation. Some of these standards do not support semantic interoperability completely, some others are poor community support, and some of them do not provide the required level of security. Table 4 shows some of each standard advantages and disadvantages.
An approach to finding good anchor nodes in ontologies
Published in International Journal of Computers and Applications, 2019
Zhiqiang (John) Wu, Sampson Gholston, Letha Etzkorn
Ontologies may be used for domain knowledge reusing, sharing, and interchanging. Ontologies are explicitly defined and are machine processable. They have been made machine processable through the use of multiple ontology representation languages, including conceptual graphs and RDF/OWL. The web ontology language (OWL), for example, is the ontology representation language that is most used for the World Wide Web. It is considered to be ‘an important step for making data on the Web more machine processable and reusable across applications [5].’ The W3C Web Ontology Working Group developed OWL to be used as a knowledge modeling language for ontologies used on the web [5].