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Semantic Web Technologies
Published in Archana Patel, Narayan C. Debnath, Bharat Bhushan, Semantic Web Technologies, 2023
Esingbemi P. Ebietomere, Godspower O. Ekuobase
The Resource Description Framework (RDF) is a data model that came with the advent of the semantic web and is consequently referred to as the first layer of the semantic web proper [5]. This model is represented as a triple in the form of subject, predicate, and object—with the predicate sometimes referred to as property [33–36]. The constituents of the RDF data model are the RDF terms that can be used in reference to resources. This term in itself consists of three disjoint subsets; the IRIs, blank nodes, and literals [31,37]. It is pertinent to note that not all resources are assigned IRI and literals, thus, the existence of such resources are denoted with variables known as blank nodes. Literals are simply a set of lexical values. For clarity purposes, let us assume I is the set of all IRIs, B is a set of blank nodes, L is a set of literals, and t denotes a triple. Then, the RDF triple may be defined as t = <s, p, o>, where s Є I U B, p Є I, and o Є I U B U L. Furthermore, a collection of RDF triples may be viewed as a labeled multi-graph where the subjects and the objects are the nodes in the graph and the properties posing as connectors between the nodes to form an edge shown as s→po [36].
Semantic Annotation of Healthcare Data
Published in Saravanan Krishnan, Ramesh Kesavan, B. Surendiran, G. S. Mahalakshmi, Handbook of Artificial Intelligence in Biomedical Engineering, 2021
M. Manonmani, Sarojini Balakrishanan
In a semantic annotation model, the meanings and relations of the data terms are delivered to the computer using ontology objects that, in fact, enriches resource information. Web Ontology Language (OWL) is considered as a standard language for ontology representation for semantic web (Jabbar et al., 2017). The proposed research work is implemented on Protégé 5.0 ontology editor. The Protégé 5.0 ontology editor provides various options for querying and structuring. The query process inbuilt in the Portege tool enables the users to perform a detailed analysis of the input and output data. The results of the semantic annotation process are an OWL instance file, which is available to the end-users of the system and the output file can be processed further for more pattern analysis and knowledge discovery.
Ontology-Based Information Retrieval and Matching in IoT Applications
Published in Brojo Kishore Mishra, Raghvendra Kumar, Natural Language Processing in Artificial Intelligence, 2020
M. Lawanya Shri, E. Ganga Devi, Balamurugan Balusamy, Jyotir Moy Chatterjee
Also, the most emerging phase of IoT is to enhance a suitable architecture, where the functions, data process, and message transfer models can be designed to model and control the transactions. In the existing system, the research based on the semantic web was made to join the AI and knowledge engineering to demonstrate and to process the data and knowledge. The meaningful technology with all the descriptions by machines provides a method to explain the heterogeneous objects, information sharing, and integration issues. The semantic web technologies are ontology, semantic annotation, bond information, and semantic web services [51], which are used as an important solution to observe the sharing of semantic information between IoT entities. Of all these, the various studies are Task Computing based middleware [52], Smart Semantic middleware [53], and Semantic Device bus [54].
Digitalisation and servitisation of machine tools in the era of Industry 4.0: a review
Published in International Journal of Production Research, 2023
Ontology is a technology that formally represents knowledge as a set of concepts within a domain (Lu et al. 2014). It has classes that represent things in reality, properties that give details to classes, and restrictions that create rules for the ontology (Järvenpää et al. 2019). OWL is the most used semantic web language for developing ontology models. SWRL and SPARQL query language are frequently used for generating rules and querying knowledge from the ontology models. In the field of manufacturing, ontology has been widely used for modelling various types of manufacturing resources and processes (Usman et al. 2013). For machine tools, some existing standards such as STEP (ISO 10303-238/242) and STEP-NC (ISO 14619-201) that are dedicated to describing machine tools and machining processes have also been used as references to develop information models for machine tools (Um, Suh, and Stroud 2016). Figure 11(c,d) shows two examples of ontology-based and STEP-NC-based machine tool information models, respectively. Knowledge-oriented machine tool information models contain rich knowledge about the property, capability, and functionality of machine tools and machining processes. Hence, they are commonly used to perform decision-making tasks such as machine tool selection, process planning, and fault diagnostics. Representative research works on knowledge-oriented machine tool information models are summarised in Table 5.
EPCI: An Embedding Method for Post-Correction of Inconsistency in the RDF Knowledge Bases
Published in IETE Journal of Research, 2022
Farhad Abedini, Mohammad Reza Keyvanpour, Mohammad Bagher Menhaj
The Resource Description Framework (RDF) is a standard data model for the data change in the web, which is designed for implementation of the semantic web and presented in 1999 by the World Wide Web Consortium (W3C) [41]. This data model helps to display the existing facts on the web structurally so that they can be processed more easily. The collection of these facts is stored in a KB as RDF data. The RDF KBs are composed of RDF datasets as a series of triples, each of which is called a fact (). Each fact contains two entities and a relation between these entities. The first entity is called subject (), the second entity is the object (), and the relation between them is named predicate () [22]. For example, the fact “Ali Parvin was born in Tehran” can be shown with the triple of (s, p, o) = (AliParvin, bornIn, Tehran) in which “Ali Parvin” is first entity, “Tehran” is the second entity and the “born in” is the relation between these two entities. As an example, a part of the triples of an RDF KB is given in Table 1.
Knowledge on-demand: a function of the future spatial knowledge infrastructure
Published in Journal of Spatial Science, 2021
Lesley M. Arnold, David A. McMeekin, Ivana Ivánová, Kylie Armstrong
The Semantic Web is a Web of Data where the data is self-describing, that is, structured in a way that it can be machine processed with meaning automatically derived. The Resource Description Framework (RDF) format (W3C 2014b) combined with Linked Open Data (Berners-Lee 2006) facilitate structured data links to be established allowing for the meaning to be discovered within the data. With the semantics held within the data, Web resources can be harnessed for automated processing (Sheth et al. 2005). Thus, with Semantic Web technologies, end users have the ability to mobilise a broad range of spatial resources via an open query interface to extract the available knowledge from the data. This has the potential to be done without having to configure systems specifically the end users.