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Song, Lan, Li Xia Lei, Hong Wang, and Jun Hong Hua. "Research on Ontology-Based Semantic Reasoning." Advanced Materials Research 171-172 (December 2010): 136–39. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.136.
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As a new emerging web, semantic web, has recently drawn considerable attention from both academic and industry field. Nowadays, RDF, RDF Schema, OWL etc. have become commonly used languages in the Semantic Web. This paper describes the ontology language and description logic, shows the relationship of them, and finally presents a reasoning path for transitive closure in an ontology document.
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Wang, Gang, Jie Lin, Qing Qi Long, and Zhi Juan Hu. "OWL-Based Description for Agent." Advanced Materials Research 217-218 (March 2011): 1218–23. http://dx.doi.org/10.4028/www.scientific.net/amr.217-218.1218.
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This paper presents a detailed formal specification of agents and their properties and abilities,based on the Web Ontology Language (OWL). It allows an agent to be specified entirely using standard mark-up languages from the Semantic Web community, namely RDF, RDF Schemaand OWL. The basic agent components are identified and their implementation using ontology development tools is described.The description improves consistency, interoperability and maintainability of agent program. Therefore,the design errors in the early development stages could be efficiently detected and avoided.
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Wang, Wen Li, Min Huang, and Ying Wang. "Construction of XBRL Semantic Metamodel and Knowledge Base Based on Ontology." Applied Mechanics and Materials 571-572 (June 2014): 1119–28. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.1119.
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In order to improve the interoperability of XBRL format financial reporting on the semantic level, a novel XBRL financial reporting metamodel and a fact data semantic metamodel are proposed, which uses the Semantic Web technologies and Ontology theory. Then, a XBRL knowledge base is constructed based on this metamodel .Using the metamodel-based translation mechanism from XBRL to OWL / RDF, all the semantic information in XBRL taxonomy and instance documents is translated into OWL ontology and RDF instance. Finally, a knowledge base covering the semantic information of financial reporting domain is constructed.
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Sequeda, Juan F., Syed Hamid Tirmizi, Oscar Corcho, and Daniel P. Miranker. "Survey of directly mapping SQL databases to the Semantic Web." Knowledge Engineering Review 26, no. 4 (December 2011): 445–86. http://dx.doi.org/10.1017/s0269888911000208.
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AbstractThe Semantic Web anticipates integrated access to a large number of information sources on the Internet represented as Resource Description Framework (RDF). Given the large number of websites that are backed by SQL databases, methods that automate the translation of those databases to RDF are crucial. One approach, taken by a number of researchers, is to directly map the SQL schema to an equivalent Web Ontology Language (OWL) or RDF Schema representation, which in turn, implies an RDF representation for the relational data. This paper reviews this research, and derives a consolidated, overarching set of translation rules expressible as a stratified Datalog program. We present all the possible key combinations in an SQL schema and consider their implied semantic properties. We review the approaches and characterize them with respect to the scope of their coverage of SQL constructs.
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Nurmikko-Fuller, Terhi, Daniel Bangert, Alan Dix, David Weigl, and Kevin Page. "Building Prototypes Aggregating Musicological Datasets on the Semantic Web." Bibliothek Forschung und Praxis 42, no. 2 (June 1, 2018): 206–21. http://dx.doi.org/10.1515/bfp-2018-0025.
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Abstract Semantic Web technologies such as RDF, OWL, and SPARQL can be successfully used to bridge complementary musicological information. In this paper, we describe, compare, and evaluate the datasets and workflows used to create two such aggregator projects: In Collaboration with In Concert, and JazzCats, both of which bring together a cluster of smaller projects containing concert and performance metadata.
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Viola, Fabio, Luca Roffia, Francesco Antoniazzi, Alfredo D’Elia, Cristiano Aguzzi, and Tullio Salmon Cinotti. "Interactive 3D Exploration of RDF Graphs through Semantic Planes." Future Internet 10, no. 8 (August 17, 2018): 81. http://dx.doi.org/10.3390/fi10080081.
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This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.
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Sireteanu, Alexandru Napoleon. "A Survey of Web Ontology Languages and Semantic Web Services." Annals of the Alexandru Ioan Cuza University - Economics 60, no. 1 (July 1, 2013): 42–53. http://dx.doi.org/10.2478/aicue-2013-0005.
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Abstract In the beginning World Wide Web was syntactic and the content itself was only readable by humans. The modern web combines existing web technologies with knowledge representation formalisms. In this sense, the Semantic Web proposes the mark-up of content on the web using formal ontology that structure essential data for the purpose of comprehensive machine understanding. On the syntactical level, standardization is an important topic. Many standards which can be used to integrate different information sources have evolved. Beside the classical database interfaces like ODBC, web-oriented standard languages like HTML, XML, RDF and OWL increase in importance. As the World Wide Web offers the greatest potential for sharing information, we will base our paper on these evolving standards.
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SCHLICHT, ANNE, and HEINER STUCKENSCHMIDT. "PEER-TO-PEER REASONING FOR INTERLINKED ONTOLOGIES." International Journal of Semantic Computing 04, no. 01 (March 2010): 27–58. http://dx.doi.org/10.1142/s1793351x10000948.
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The Semantic Web is commonly perceived as a web of partially-interlinked machine readable data. This data is inherently distributed and resembles the structure of the web in terms of resources being provided by different parties at different physical locations. A number of infrastructures for storing and querying distributed semantic web data, primarily encoded in RDF have been developed. While there are first attempts for integrating RDF Schema reasoning into distributed query processing, almost all the work on description logic reasoning as a basis for implementing inference in the Web Ontology Language OWL still assumes a centralized approach where the complete terminology has to be present on a single system and all inference steps are carried out on this system. We have designed and implemented a distributed reasoning method that preserves soundness and completeness of reasoning under the original OWL import semantics and has beneficial properties regarding parallel computation and overhead caused by communication effort and additional derivations. The method is based on sound and complete resolution methods for the description logic [Formula: see text] that we modify to work in a distributed setting.
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Khamis, Khamis Abdul Latif, Luo Zhong, and Hua Zhu Song. "Study on Digital Content Representation from Direct Label Graph to RDF/OWL Language into Semantic Web." Applied Mechanics and Materials 644-650 (September 2014): 3304–9. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3304.
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An increasing number of publication and consumptions of media data on the social and dynamic web has allowed ontology technology to grow up unpredictable. News agencies, cultural heritage sites, social media companies and ordinary users contribute a large portion of media contents across web community. These huge amounts of media contents are generally accessed via standardized and proprietary metadata formats through semantic web. But nearly all cases need specific, standardized, and more expressive methods to represent media data into the knowledge representation paradigm. This paper proposes the proper methods to express media ontology based on the nature of media data. At first RDF graph representation model is used to show the expressive power of domain classification with direct label graph concepts. Secondly, events and object class domain are used to express relational properties of media content. Finally, the events and object class domain is expressed into RDF/OWL language, as preferable and standardized language to represent media data in the semantic web.
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Yeh, Ching-Long, Chun-Fu Chang, and Po-Shen Lin. "Ontology-Based Personal Annotation Management on Semantic Peer Network to Facilitating Collaborations in e-Learning." International Journal of Handheld Computing Research 2, no. 2 (April 2011): 20–33. http://dx.doi.org/10.4018/jhcr.2011040102.
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The trend of services on the web is making use of resources on the web collaborative. Semantic Web technology is used to build an integrated infrastructure for the new services. This paper develops a distributed knowledge based system using the RDF/OWL technology on peer-to-peer networks to provide the basis of building personal social collaboration services for e-Learning. This paper extends the current tools accompanied with lecture content to become annotation sharable using the distributed knowledge base.
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LAM, TOBY H. W., JAMES N. K. LIU, and RAYMOND S. T. LEE. "MASTER: AN INTELLIGENT ONTOLOGY-BASED MULTI-AGENT SYSTEM FOR SIGHTSEER." International Journal of Software Engineering and Knowledge Engineering 19, no. 02 (March 2009): 137–57. http://dx.doi.org/10.1142/s021819400900412x.
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Recently, semantic web has received substantial attention from the research community. Semantic web aims to provide a new framework that can enable knowledge sharing and reusing. Semantic web is a collection of web technologies that include a number of markup languages such as RDF, OWL and RDFS. These markup languages are used for modeling a domain ontology. By using ontology to model resources, humans and computers (software agents) can have a consensus on the resource structure. The use of these technologies allows the creation of a more effective web search system. In this paper, we modeled travel domain ontology by using Web Ontology Language (OWL). Instead of inviting an expert to model the ontology, we created the travel ontology by collecting and analyzing the structural information from a number of travel related websites. Besides, we implemented an intelligent ontology-based Multi-Agent System for sighTseER (MASTER), which is constructed by using semantic web technologies. MASTER integrates Global Positioning System (GPS), ontology and agent technologies to support location awareness for providing the precise navigation and classify the tourist information for the users. The system was tested on 30 novice users. 83% of the users felt that the system can help tourists find tourist information in Hong Kong.
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Gasevic, Dragan. "Petri nets on the semantic web guidelines and infrastructure." Computer Science and Information Systems 1, no. 2 (2004): 127–51. http://dx.doi.org/10.2298/csis0402127g.
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This paper gives the Petri net ontology as the most important element in providing Petri net support for the Semantic Web. Available Petri net formal descriptions are: metamodels, UML profiles, ontologies and syntax. Metamodels are useful, but their main purpose is for Petri net tools. Although the current Petri-net community effort Petri Net Markup Language (PNML) is XML-based, it lacks a precise definition of semantics. Existing Petri net ontologies are partial solutions specialized for a specific problem. In order to show current Petri net model sharing features we use P3 tool that uses PNML/XSLT-based approach for model sharing. This paper suggests developing the Petri net ontology to represent semantics appropriately. This Petri net ontology is described using UML, Resource Description Framework (Schema) RDF(S) and the Web Ontology Language-OWL.
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Melo, Dora, Irene Pimenta Rodrigues, and Vitor Beires Nogueira. "Work Out the Semantic Web Search: The Cooperative Way." Advances in Artificial Intelligence 2012 (August 2, 2012): 1–9. http://dx.doi.org/10.1155/2012/867831.
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We propose a Cooperative Question Answering System that takes as input natural language queries and is able to return a cooperative answer based on semantic web resources, more specifically DBpedia represented in OWL/RDF as knowledge base and WordNet to build similar questions. Our system resorts to ontologies not only for reasoning but also to find answers and is independent of prior knowledge of the semantic resources by the user. The natural language question is translated into its semantic representation and then answered by consulting the semantics sources of information. The system is able to clarify the problems of ambiguity and helps finding the path to the correct answer. If there are multiple answers to the question posed (or to the similar questions for which DBpedia contains answers), they will be grouped according to their semantic meaning, providing a more cooperative and clarified answer to the user.
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Métral, C., and G. Falquet. "EXTENSION AND CONTEXTUALISATION FOR LINKED SEMANTIC 3D GEODATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W10 (September 12, 2018): 113–18. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w10-113-2018.
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<p><strong>Abstract.</strong> The application of the linked data principles provide a simple and effective way to publish and share data on the Web. The publication of geodata on the Web bas been studied and developed for a long time, leading to the creation of geo vocabularies and ontologies as well as geographic query languages. This is also true for 3D geodata, for which multiple RDF vocabularies and OWL ontologies exist (at the building, city, or territory level). In this paper we show that at least two issues remain to be addressed to reach a satisfactory publication framework for 3D linked geodata. First, the semantic model interconnection issue is not magically solved by the creation of ontologies, it requires the careful design of interconnection and extension schemes and their management. Second, the representation of additional dimensions, such as time, level of detail, confidence level, provenance, etc. cannot be directly handled in RDF. For these two issues we propose methodologies and design patterns and show how they can actually be used to create a semantically rich representation of 3D or nD linked geodata.</p>
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Bouougada, Benamar, Djelloul Bouchiha, Abdelghani Bouziane, and Mimoun Malki. "Ontology Authoring and Linked Data Generation from Web Applications." International Journal of Strategic Information Technology and Applications 8, no. 4 (October 2017): 52–66. http://dx.doi.org/10.4018/ijsita.2017100105.
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One of the fundamental problems in the development of the semantic web is what is known as the ontology authoring. This process allows the domain expert to create ontologies and their instances by dedicated tools from relational databases and/or web applications. In this article is presented an approach that allows building OWL ontologies and RDF instances from web applications. The proposed approach starts with a reverse engineering process that aims to recover the original design from the web application source code by using program understanding techniques. Then, a forward engineering process is applied to create an OWL ontology from the recovered diagrams, based on a set of mapping rules. The proposed approach is concertized by a PHP2OWLGen tool and is evaluated with a set of web applications. The obtained results were encouraging and showed the efficiency of the proposed approach.
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Narayana Bhat, Talapady, and John Barkley. "Development of a use Case for Chemical Resource Description Framework for Acquired Immune Deficiency Syndrome Drug Discovery." Open Bioinformatics Journal 2, no. 1 (July 2, 2008): 20–27. http://dx.doi.org/10.2174/1875036200802010020.
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There is considerable interest in RDF (Resource Description Framework) as a data representation standard for the growing information technology needs of drug discovery. Though several efforts towards this goal have been reported, most of the reported efforts have focused on text-based data. Structural data of chemicals are a key component of drug discovery and molecular images may offer certain advantages over text-based representations for them. Here we discuss the steps that we used to develop and search chemical Resource Description Framework (RDF) using text and image for structures of relevant to Acquired Immune Deficiency Syndrome (AIDS). These steps are (a) acquisition of the data on drugs, (b) definition of the framework to establish RDF on drugs using commonly asked questions during a drug discovery effort, (c) annotation of the structural data on drugs into RDF using the framework established in step (b), (d) validation of the annotation methods using Semantic Web concepts and tools, (e) design and development of public Web to distribute data to the public, (f) generation and distribution of data using OWL (Web Ontology Language). This paper describes this effort, discusses our observations and announces the availability of the OWL model at the W3C Web site (http://esw.w3.org/topic/HCLS/ChemicalTaxonomiesUseCase). The style of this paper is chosen so as to cover a broad audience including structural biologists, medicinal chemists, and information technologists and at times may appear say to the obvious for certain experts. A full discussion of our method and its comparison to other published methods is beyond the scope of this publication.
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Wei, Bingyang, and Jing Sun. "Leveraging SPARQL Queries for UML Consistency Checking." International Journal of Software Engineering and Knowledge Engineering 31, no. 04 (April 2021): 635–54. http://dx.doi.org/10.1142/s0218194021500170.
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Context and motivation: Multiple-viewed requirements modeling method describes the system to-be from different perspectives. Some requirements models are then specified in various UML diagrams. Question/problem: Managing those models can be tedious and error-prone, since a lot of CASE tools provide poor support for reasoning and consistency checking. Principal ideas/results: Ontology is a formal notation for describing concepts and their relations in a domain. Since software requirements are a kind of knowledge, we propose to adopt a knowledge engineering approach for managing the consistency of requirements models. In this paper, an ontology for three most commonly used UML diagrams is developed in Web Ontology Language (OWL). The transformation of UML class, sequence and state diagrams to OWL knowledge base is presented. Owing to the underlying logical reasoning capability of OWL, a semantic query language, SPARQL (SPARQL Protocol and RDF Query Language), is used to query the knowledge base for consistency checking. Contribution: This paper introduces a semantic web-based knowledge engineering approach to represent and manage software requirements knowledge in OWL. By experimenting with a concrete software system, we demonstrate the feasibility and applicability of this knowledge approach.
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Gan, Jian Hou, and Ling Yun Yuan. "Study on Knowledge Base Construction for the Network Teaching Resource Based on Semantic Web." Applied Mechanics and Materials 16-19 (October 2009): 758–63. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.758.
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Intelligent teaching system design has become an active research topic in education research community. How to manage the network teaching resource efficiently will have a direct impact on the teaching process and quality in the network teaching system. The semantic web can be a very promising platform for knowledge management systems in the intelligent teaching system design. In this paper, we have presented a framework for the network teaching resource knowledge base (NTRKB) based on semantic web, which includes network teaching resource knowledge representation, regular relation definition based on OWL, knowledge base modeling and construction based on RDF. The NTRKB can achieve knowledge sharing and intelligent retrieval for the network teaching resource, and these components will greatly benefit the development of the proposed intelligent teaching system.
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Rivault, Y., O. Dameron, and N. Le Meur. "queryMed: Semantic Web functions for linking pharmacological and medical knowledge to data." Bioinformatics 35, no. 17 (January 18, 2019): 3203–5. http://dx.doi.org/10.1093/bioinformatics/btz034.
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AbstractSummaryIn public health research and more precisely in the reuse of electronic health data, selecting patients, identifying specific events and interpreting results typically requires biomedical knowledge. The queryMed R package aims to facilitate the integration of medical and pharmacological knowledge stored in formats compliant with the Linked Data paradigm (e.g. OWL ontologies and RDF datasets) into the R statistical programming environment. We show how it allowed us to identify all the drugs prescribed for critical limb ischemia (CLI) and also to detect one contraindicated prescription for one patient by linking a medical database of 1003 CLI patients to ontologies.Availability and implementationqueryMed is readily usable for medical data mappings and enrichment. Sources, R vignettes and test data are available on GitHub (https://github.com/yannrivault/queryMed) and are archived on Zenodo (https://doi.org/10.5281/zenodo.1323481).
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DOU, DEJING, HAN QIN, and PAEA LEPENDU. "ONTOGRATE: TOWARDS AUTOMATIC INTEGRATION FOR RELATIONAL DATABASES AND THE SEMANTIC WEB THROUGH AN ONTOLOGY-BASED FRAMEWORK." International Journal of Semantic Computing 04, no. 01 (March 2010): 123–51. http://dx.doi.org/10.1142/s1793351x10000961.
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Integrating existing relational databases with ontology-based systems is among the important research problems for the Semantic Web. We have designed a comprehensive framework called OntoGrate which combines a highly automatic mapping system, a logic inference engine, and several syntax wrappers that inter-operate with consistent semantics to answer ontology-based queries using the data from heterogeneous databases. There are several major contributions of our OntoGrate research: (i) we designed an ontology-based framework that provides a unified semantics for mapping discovery and query translation by transforming database schemas to Semantic Web ontologies; (ii) we developed a highly automatic ontology mapping system which leverages object reconciliation and multi-relational data mining techniques; (iii) we developed an inference-based query translation algorithm and several syntax wrappers which can translate queries and answers between relational databases and the Semantic Web. The testing results of our implemented OntoGrate system in different domains show that the large amount of data in relational databases can be directly utilized for answering Semantic Web queries rather than first converting all relational data into RDF or OWL.
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Jajaga, Edmond, and Lule Ahmedi. "C-SWRL: A Unique Semantic Web Framework for Reasoning Over Stream Data." International Journal of Semantic Computing 11, no. 03 (September 2017): 391–409. http://dx.doi.org/10.1142/s1793351x17400165.
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The synergy of Data Stream Management Systems and Semantic Web applications has steered towards a new paradigm known as Stream Reasoning. The Semantic Web standards for knowledge base modeling and querying, namely RDF, OWL and SPARQL, has extensively been used by the Stream Reasoning community. However, the Semantic Web rule languages, such as SWRL and RIF, have never been used in stream data applications. Instead, different non-Semantic Web rule systems have been approached. Since RIF is primarily intended for exchanging rules among systems, we focused on SWRL applications with stream data. This proves difficult following the SWRL’s open world semantics. To overcome SWRL’s expressivity issues we propose an infrastructure extension, which will enable SWRL reasoning with stream data. Namely, a query processing system, such as C-SPARQL, was layered under SWRL to support closed-world and time-aware reasoning. Moreover, OWLAPI constructs were utilized to enable non-monotonicity, while SPARQL constructs were used to enable negation as failure. Water quality monitoring was used as a validation domain of the proposed system.
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Lorenzo, Jorge González, José Emilio Labra Gayo, and José María Álvarez Rodríguez. "A MapReduce Implementation of the Spreading Activation Algorithm for Processing Large Knowledge Bases Based on Semantic Networks." International Journal of Knowledge Society Research 3, no. 4 (October 2012): 47–56. http://dx.doi.org/10.4018/jksr.2012100105.
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The emerging Web of Data as part of the Semantic Web initiative and the sheer mass of information now available make it possible the deployment of new services and applications based on the reuse of existing vocabularies and datasets. A huge amount of this information is published by governments and organizations using semantic web languages and formats such as RDF, implicit graph structures developed using W3C standard languages: RDF-Schema or OWL, but new flexible programming models to process and exploit this data are required. In that sense the use of algorithms such as Spreading Activation is growing in order to find relevant and related information in this new data realm. Nevertheless the efficient exploration of the large knowledge bases has not yet been resolved and that is why new paradigms are emerging to boost the definitive deployment of the Web of Data. This cornerstone is being addressed applying new programming models such as MapReduce in combination with old-fashioned techniques of Document and Information Retrieval. In this paper an implementation of the Spreading Activation technique based on the MapReduce programming model and the problems of applying this paradigm to graph-based structures are introduced. Finally, a concrete experiment with real data is presented to illustrate the algorithm performance and scalability.
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Biletskiy, Yevgen, Harold Boley, Girish R. Ranganathan, and Harold Boley. "RuleML‐based learning object interoperability on the Semantic Web." Interactive Technology and Smart Education 5, no. 1 (February 1, 2008): 39–58. http://dx.doi.org/10.1108/17415650810871574.
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PurposeThe present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions.Design/methodology/approachAs proof of concept, a rule set is implemented using the rule markup language (RuleML), a member of XML‐based languages. This representation in RuleML allows the rule base to be platform‐independent, flexibly extensible and executable.FindingsThe RuleML source representation is easily converted to other XML‐based languages (such as RDF, OWL and XMI) as well as incorporated into, and extracted from, existing XML‐based repositories (such as IEEE LOM and CanLOM) using XSL Transformations (XSLT).Practical implicationsThe RuleML facts and rules represented in the positional slotted language are used by the OO jDREW reasoning engine to detect and map between semantically equivalent components of course outlines as the key step in their interoperation. In particular, this will enable the precise delivery of learning objects (e.g. course outlines) from repositories to a specific learner's context.Originality/valueAlthough the particular scenario is discussed in the present paper, the proposed approach can be applied to other tasks related to enabling semantic interoperability.
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Jetlund, K. "IMPROVEMENTS IN AUTOMATED DERIVATION OF OWL ONTOLOGIES FROM GEOSPATIAL UML MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 283–90. http://dx.doi.org/10.5194/isprs-archives-xlii-4-283-2018.
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<p><strong>Abstract.</strong> Standards from ISO/TC 211 are the foundation for modelling a universe of discourse in a geospatial context. UML models based on the standards, and in particular based on the UML profile defined in ISO 19103, have been developed and implemented in applications and databases for a wide range of geospatial information, from international to national and agency level. Amounts of information has been collected, maintained and made available based on the models, but mainly through specific services and exchange formats for geospatial information. To make the models and the information available in The Semantic Web, the geospatial UML models need to be transformed from UML to OWL ontologies, and the information needs to be transformed from UML-based structures to RDF triples. This paper investigates methods for transforming UML models of geospatial information to OWL ontologies, identifies challenges, suggest improvements and identifies needs for further research. Several methods for automated transformation from geospatial UML models to OWL handle basic concepts, but some concepts and context-closed restrictions from UML cannot be directly transformed to the open world of The Semantic Web. None of the analysed methods handles all of these issues, and suggested improvements include combining and improving transformation rules, as well as modifications in the UML models. To what degree and how these issues need to be handled will depend on whether the scope of the ontologies is to simply present geospatial information on The Semantic Web, or if they shall be used in a bidirectional information exchange.</p>
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Bassiliades, Nick. "A Tool for Transforming Semantic Web Rule Language to SPARQL Infererecing Notation." International Journal on Semantic Web and Information Systems 16, no. 1 (January 2020): 87–115. http://dx.doi.org/10.4018/ijswis.2020010105.
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Semantic web rule language (SWRL) combines web ontology language (OWL) ontologies with horn logic rules of the rule markup language (RuleML) family. Being supported by ontology editors, rule engines and ontology reasoners, it has become a very popular choice for developing rule-based applications on top of ontologies. However, SWRL is probably not going to become a WWW Consortium standard, prohibiting industrial acceptance. On the other hand, SPARQL Inferencing Notation (SPIN) has become a de-facto industry standard to represent SPARQL rules and constraints on semantic web models, building on the widespread acceptance of SPARQL (SPARQL Protocol and RDF Query Language). In this article, we argue that the life of existing SWRL rule-based ontology applications can be prolonged by converting them to SPIN. To this end, we have developed the SWRL2SPIN tool in Prolog that transforms SWRL rules into SPIN rules, considering the object-orientation of SPIN, i.e. linking rules to the appropriate ontology classes and optimizing them, as derived by analysing the rule conditions.
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Agarwal, Prakhar, and Shivani Jain. "Semantic web: golden era of information." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 436. http://dx.doi.org/10.14419/ijet.v7i2.8.10477.
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Semantic Web is the extension of existing web that allows well defined expressions for the meaning of information which can be understood by computers and people both. In this paper we are doing study on semantic and is our review paper. Semantic web is a recommended development project by W3C (World Wide Web Consortium) which focuses on the enhancing of information search by keeping the facts in structured form using eXtensible Mark-up Language (XML) and marked in such a way that it can be understand by the system. To make the development of semantic web promising, new international standard is developed for exchanging of ontologies called OWL Web Ontology language. In XML we just provide tag of the model and store data in the hierarchy without its meaning, that’s why the computer cannot be able to process the data but in Semantic Web user can provide with a definition so that the computer can better recognize its meaning and provide with the better displaying of information. A crux of semantic web is that it works on the definition of the ontologies. Ontologies are responsible for re-usability and sharing of information. Semantic Web provides with a shared language which has stored data in the non-ending linking of distinct databases which provides data related to the real world objects. RDF is a common language for semantic web and is responsible for the collection of data on web and assembles different database from diverse sources and SPARQL is there for linking of databases for unifying documents. Thus, semantic web is the well-structured data web that relates all the data that present on the web and understands them to provide the exact display requested by the end user.
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Pellen, Florian, Sylvain Bouquin, Isabelle Mougenot, and Régine Vignes-Lebbe. "Building an OWL ontology with Xper3." Biodiversity Information Science and Standards 2 (May 21, 2018): e25614. http://dx.doi.org/10.3897/biss.2.25614.
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Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.
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Holford, Matthew E., Haseena Rajeevan, Hongyu Zhao, Kenneth K. Kidd, and Kei-Hoi Cheung. "Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data." Cancer Informatics 8 (January 2009): CIN.S1006. http://dx.doi.org/10.4137/cin.s1006.
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We demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the exploitation of pathway knowledge for cancer drug discovery. We model our data using the Web Ontology Language (OWL), drawing upon ideas from existing standard formats BioPAX for pathway data and PML for allele frequency data. We store our data within an Oracle database, using Oracle Semantic Technologies. We then query the data using Oracle's rule-based inference engine and SPARQL-like RDF query language. The ability to perform queries across the domains of population genetics and pathways offers the potential to answer a number of cancer-related research questions. Among the possibilities is the ability to identify genetic variants which are associated with cancer pathways and whose frequency varies significantly between ethnic groups. This sort of information could be useful for designing clinical studies and for providing background data in personalized medicine. It could also assist with the interpretation of genetic analysis results such as those from genome-wide association studies.
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Rychtyckyj, Nestor, Venkatesh Raman, Baskaran Sankaranarayanan, P. Sreenivasa Kuma, and Deepak Khemani. "Ontology Re-Engineering: A Case Study from the Automotive Industry." AI Magazine 38, no. 1 (March 31, 2017): 49–60. http://dx.doi.org/10.1609/aimag.v38i1.2712.
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For over twenty-five years Ford Motor Company has been utilizing an AI-based system to manage process planning for vehicle assembly at its assembly plants around the world. The scope of the AI system, known originally as the Direct Labor Management System and now as the Global Study Process Allocation System (GSPAS), has increased over the years to include additional functionality on Ergonomics and Powertrain Assembly (Engines and Transmission plants). The knowledge about Ford’s manufacturing processes is contained in an ontology originally developed using the KL-ONE representation language and methodology. To preserve the viability of the GSPAS ontology and to make it easily usable for other applications within Ford, we needed to re-engineer and convert the KL-ONE ontology into a semantic web OWL/RDF format. In this article, we will discuss the process by which we re-engineered the existing GSPAS KL-ONE ontology and deployed semantic web technology in our application.
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Al Agha, I., and O. El-Radie. "Towards Verbalizing SPARQL Queries in Arabic." Engineering, Technology & Applied Science Research 6, no. 2 (April 17, 2016): 937–44. http://dx.doi.org/10.48084/etasr.630.
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With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.
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Maleewong, Krissada, Chutiporn Anutariya, and Vilas Wuwongse. "Enabling Intelligence in Web-Based Collaborative Knowledge Management System." International Journal of Systems and Service-Oriented Engineering 2, no. 1 (January 2011): 40–59. http://dx.doi.org/10.4018/jssoe.2011010103.
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This paper presents an approach to enhance various intelligent services of a Web-based collaborative knowledge management system. The proposed approach applies the two widely-used argumentation technologies, namely IBIS and Toulmin’s argumentation schemes, to structurally capture the deliberation and collaboration occurred during the consensual knowledge creation process. It employs RDF and OWL as its underlying knowledge representation language with well-defined semantics and reasoning mechanisms. Users can easily create knowledge using a simple corresponding graphical notation with machine-processable semantics. Derivation of implicit knowledge, similar concept discovery, as well as semantic search, are also enabled. In addition, the proposed approach incorporates the term suggestion function for assisting users in the knowledge creation process by computing the relevance score for each relevant term, and presenting the most relevant terms to users for possible term reusing or equivalence concepts mapping. To ensure the knowledge consistency, a logical mechanism for validating conflicting arguments and contradicting concepts is also developed. Founded on the proposed approach, a Web-based system, namely ciSAM, is implemented and available for public usage.
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Bona, Jonathan P., Fred W. Prior, Meredith N. Zozus, and Mathias Brochhausen. "Enhancing Clinical Data and Clinical Research Data with Biomedical Ontologies - Insights from the Knowledge Representation Perspective." Yearbook of Medical Informatics 28, no. 01 (August 2019): 140–51. http://dx.doi.org/10.1055/s-0039-1677912.
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Objectives: There exists a communication gap between the biomedical informatics community on one side and the computer science/artificial intelligence community on the other side regarding the meaning of the terms “semantic integration" and “knowledge representation“. This gap leads to approaches that attempt to provide one-to-one mappings between data elements and biomedical ontologies. Our aim is to clarify the representational differences between traditional data management and semantic-web-based data management by providing use cases of clinical data and clinical research data re-representation. We discuss how and why one-to-one mappings limit the advantages of using Semantic Web Technologies (SWTs). Methods: We employ commonly used SWTs, such as Resource Description Framework (RDF) and Ontology Web Language (OWL). We reuse pre-existing ontologies and ensure shared ontological commitment by selecting ontologies from a framework that fosters community-driven collaborative ontology development for biomedicine following the same set of principles. Results: We demonstrate the results of providing SWT-compliant re-representation of data elements from two independent projects managing clinical data and clinical research data. Our results show how one-to-one mappings would hinder the exploitation of the advantages provided by using SWT. Conclusions: We conclude that SWT-compliant re-representation is an indispensable step, if using the full potential of SWT is the goal. Rather than providing one-to-one mappings, developers should provide documentation that links data elements to graph structures to specify the re-representation.
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Gorskis, Henrihs, and Arkady Borisov. "Storing an OWL 2 Ontology in a Relational Database Structure." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 3 (June 16, 2015): 71. http://dx.doi.org/10.17770/etr2015vol3.168.
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<p class="R-AbstractKeywords"><span lang="EN-GB">This paper examines the possibility of storing OWL 2 based ontology information in a classical relational database and reviews some existing methods for ontology databases. In most cases a database is a fitting solution for storing and sharing information among systems, clients or agents. Similarly, in order to make domain ontology information more accessible to systems, in a comparable way, it can be stored and provided in a database form. As of today, there is no consensus on a specific ontology database structure. The main focus of this paper is specifically on OWL 2 as a basis for the description of ontology centric information in a database. The Web Ontology Language OWL 2 is a language for describing ontology information for the Semantic Web. As such it consists of a list of reserved words and grammatical rules for defining many parts of ontology knowledge. Based on this language specification this paper examines the possibility of storing information in a relational database for the description of domain ontology information. By creating a database structure based on OWL2 it is feasible to obtain an approach to storing information about the domain ontology in an utilizable way, by using its descriptive abilities. Nowadays multiple approaches to storing ontology information and OWL in databases exist; most of them are based on storing RDF data or provide persistence for specific OWL software libraries. The examination of the existing approaches provided in this paper, shows how they differ from the goal of obtaining a general, more easily usable and less software library specific database for domain ontology centric information. This paper describes a version of a simple relational database capable of holding and providing ontology knowledge on demand, which can be implemented on a database management system of choice. </span></p>
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Andon, P. I., J. V. Rogushina, I. Yu Grishanova, V. A. Reznichenko, A. M. Kyridon, A. V. Aristova, and A. O. Tishchenko. "Experience of the semantic technologies use for intelligent Web encyclopedia creation (on example of the Great Ukrainian Encyclopedia portal)." PROBLEMS IN PROGRAMMING, no. 2-3 (September 2020): 246–58. http://dx.doi.org/10.15407/pp2020.02-03.246.
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We consider the conceptual principles of the Great Ukrainian Encyclopedia development and analyze the main advantages of its portal version – e-VUE. This portal version requires the relevant technological platform with high-level expressiveness and efficiency. Development of e-VUE with complex knowledge structure causes the study of modern Web-technologies and matching their capabilities with the specific requirements of encyclopedia. Therefore we consider in details the project idea and purposes, the specifics of e-VUE information representation (number and volume of articles, content types and sources, relations between content elements and their properties, business processes of article publication, design requirements) and processing (navigation, requests, integration and matching means) to estimate the Wiki-technology feasibility use (namely - opportunities and restrictions of MediaWiki technological platform). Also attention is paid to the means of information security ensuring and semantic-based establishment of content access rights. The results of such analysis show that MediaWiki with semantic plugins can be used as a base for e-VUE portal construction but needs in extension of its functionality based on modern knowledge management tools and formats of their interoperable representation. Now we are oriented on use of ontological analysis and Semantic Web standards (OWL, RDF, SPARQL). In terms of the Semantic Web, e-VUE is a distributed database with heterogeneous types of information objects that can be used both by humans and by external software (e.g. by intelligent agents). The main principles of e-VUE knowledge base organization are grounded on Wiki categories and semantic properties of Semantic MediaWiki that are used for formal representation of the e-VUE typical information objects (TIO). Such approach allows to express TIO relations, properties and characteristics that can be used by logical inference and semantic retrieval to improve the navigation between portal elements and integration of data from various Wiki pages.
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Javed, Umair, Kamran Shaukat, Ibrahim A. Hameed, Farhat Iqbal, Talha Mahboob Alam, and Suhuai Luo. "A Review of Content-Based and Context-Based Recommendation Systems." International Journal of Emerging Technologies in Learning (iJET) 16, no. 03 (February 12, 2021): 274. http://dx.doi.org/10.3991/ijet.v16i03.18851.
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In our work, we have presented two widely used recommendation systems. We have presented a context-aware recommender system to filter the items associated with user’s interests coupled with a context-based recommender system to prescribe those items. In this study, context-aware recommender systems perceive the user’s location, time, and company. The context-based recommender system retrieves patterns from World Wide Web-based on the user’s past interactions and provides future news recommendations. We have presented different techniques to support media recommendations for smartphones, to create a framework for context-aware, to filter E-learning content, and to deliver convenient news to the user. To achieve this goal, we have used content-based, collaborative filtering, a hybrid recommender system, and implemented a Web ontology language (OWL). We have also used the Resource Description Framework (RDF), JAVA, machine learning, semantic mapping rules, and natural ontology languages that suggest user items related to the search. In our work, we have used E-paper to provide users with the required news. After applying the semantic reasoning approach, we have concluded that by some means, this approach works similarly as a content-based recommender system since by taking the gain of a semantic approach, we can also recommend items according to the user’s interests. In a content-based recommender system, the system provides additional options or results that rely on the user’s ratings, appraisals, and interests.
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Hersh, W., and P. Otero. "Education in Biomedical and Health Informatics in the Web 3.0 Era: Standards for Data, Curricula, and Activities." Yearbook of Medical Informatics 20, no. 01 (August 2011): 139–41. http://dx.doi.org/10.1055/s-0038-1638752.
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SummaryWeb 3.0 is transforming the World Wide Web by allowing knowledge and reasoning to be gleaned from its content.Describe a new scenario in education and training known as “Education 3.0” that can help in the promotion of learning in health informatics in a collaborative way.Review of the current standards available for curricula and learning activities in in Biomedical and Health Informatics (BMHI) for a Web 3.0 scenario.A new scenario known as “Education 3.0” can provide open educational resources created and reused throughout different institutions and improved by means of an international collaborative knowledge powered by the use of E-learning. Currently there are standards that could be used in identifying and deliver content in education in BMHI in the semantic web era such as Resource Description Format (RDF), Web Ontology Language (OWL) and Sharable Content Object Reference Model (SCORM). In addition, there are other standards to support healthcare education and training. There are few experiences in the use of standards in e-learning in BMHI published in the literature.Web 3.0 can propose new approaches to building the BMHI workforce so there is a need to build tools as knowledge infrastructure to leverage it. The usefulness of standards in the content and competencies of training programs in BMHI needs more experience and research so as to promote the interoperability and sharing of resources in this growing discipline.
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Chatterjee, Ayan, Andreas Prinz, Martin Gerdes, and Santiago Martinez. "An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-Concept Study." Journal of Medical Internet Research 23, no. 4 (April 9, 2021): e24656. http://dx.doi.org/10.2196/24656.
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Background Lifestyle diseases, because of adverse health behavior, are the foremost cause of death worldwide. An eCoach system may encourage individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Such an eCoach system needs to collect and transform distributed heterogenous health and wellness data into meaningful information to train an artificially intelligent health risk prediction model. However, it may produce a data compatibility dilemma. Our proposed eHealth ontology can increase interoperability between different heterogeneous networks, provide situation awareness, help in data integration, and discover inferred knowledge. This “proof-of-concept” study will help sensor, questionnaire, and interview data to be more organized for health risk prediction and personalized recommendation generation targeting obesity as a study case. Objective The aim of this study is to develop an OWL-based ontology (UiA eHealth Ontology/UiAeHo) model to annotate personal, physiological, behavioral, and contextual data from heterogeneous sources (sensor, questionnaire, and interview), followed by structuring and standardizing of diverse descriptions to generate meaningful, practical, personalized, and contextual lifestyle recommendations based on the defined rules. Methods We have developed a simulator to collect dummy personal, physiological, behavioral, and contextual data related to artificial participants involved in health monitoring. We have integrated the concepts of “Semantic Sensor Network Ontology” and “Systematized Nomenclature of Medicine—Clinical Terms” to develop our proposed eHealth ontology. The ontology has been created using Protégé (version 5.x). We have used the Java-based “Jena Framework” (version 3.16) for building a semantic web application that includes resource description framework (RDF) application programming interface (API), OWL API, native tuple store (tuple database), and the SPARQL (Simple Protocol and RDF Query Language) query engine. The logical and structural consistency of the proposed ontology has been evaluated with the “HermiT 1.4.3.x” ontology reasoner available in Protégé 5.x. Results The proposed ontology has been implemented for the study case “obesity.” However, it can be extended further to other lifestyle diseases. “UiA eHealth Ontology” has been constructed using logical axioms, declaration axioms, classes, object properties, and data properties. The ontology can be visualized with “Owl Viz,” and the formal representation has been used to infer a participant’s health status using the “HermiT” reasoner. We have also developed a module for ontology verification that behaves like a rule-based decision support system to predict the probability for health risk, based on the evaluation of the results obtained from SPARQL queries. Furthermore, we discussed the potential lifestyle recommendation generation plan against adverse behavioral risks. Conclusions This study has led to the creation of a meaningful, context-specific ontology to model massive, unintuitive, raw, unstructured observations for health and wellness data (eg, sensors, interviews, questionnaires) and to annotate them with semantic metadata to create a compact, intelligible abstraction for health risk predictions for individualized recommendation generation.
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Sinaga, Arnaldo Marulitua, Rini Juliana Sipahutar, and Dian Ira Putri Hutasoit. "Penerapan Ontology Web Language pada Domain Ulos Batak Toba." Jurnal Teknologi Informasi dan Ilmu Komputer 5, no. 4 (October 1, 2018): 493. http://dx.doi.org/10.25126/jtiik.201854903.
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<p class="Abstrak">Indonesia adalah salah satu negara di dunia yang kaya akan keanekaragaman budaya. Keanekaragaman budaya ini diakibatkan banyaknya suku di Indonesia. Setiap suku memiliki kekhasan masing-masing termasuk kekhasan dalam kain tradisional. Salah satunya adalah ulos, kain tradisional suku Batak Toba. Ulos merupakan simbol sakral dalam adat istiadat suku Batak Toba. Ulos terdiri dari berbagai macam jenis, motif, warna, makna hingga fungsi. Namun sangat disayangkan bahwa informasi mengenai ulos belum terdokumentasi dengan baik. Informasi didapatkan secara turun temurun dari satu generasi ke generasi lain yang memungkinkan informasi tersebut hilang. Selain itu, beberapa sumber yang ada juga menyajikan informasi yang berbeda. Oleh karena itu, ontologi bisa menjadi salah satu solusi untuk membantu mengelola informasi yang sudah ada supaya lebih terorganisir. Ontologi membantu memformalkan semua <em>vocabulary</em> pada domain ulos. <em>Vocabulary</em> itu kemudian dalam ontologi disebut sebagai konsep. Konsep tersebut akan saling berkaitan satu sama lain sehingga dapat dilihat sebagai suatu bentuk kesatuan (<em>linked</em> data) yang membentuk pola yang terstruktur. Kondisi ini yang kemudian mendukung pencarian dengan hasil yang bernilai semantik karena pola data yang disediakan saling berkaitan satu sama lain. Ontologi tersebut dapat direprentasikan menggunakan Web Ontology Language (OWL) yang merupakan <em>vocabulary extension</em> dari Resource Descriptive Framework (RDF). Kemudian untuk proses <em>retrieving</em> data akan menggunakan SPARQL.</p><p class="Abstrak"> </p><p class="Judul2"><strong><em>Abstract</em></strong><em> </em></p><p class="Judul2" align="left"><em>Indonesia is a very rich country in cultural diversity. Most of the ethnic groups have their own uniqueness including the peculiarities in traditional textiles. One of them is Ulos, traditional cloth of Batak Toba. Ulos is a sacred symbol in the Batak traditions. Ulos consists of various types, motifs, colors, meanings and functions. However, it is unfortunate that information of Ulos has not been well documented. This cultural heritage is well-transferred from generation to generation. The existing sources sometime provide different information. Therefore, ontology can be one solution to help manage existing information to be more well-organized. Ontology helps formalize all vocabularies on the Ulos domain. The vocabulary in the ontology is called as a concept. The concepts are related to each other so that it can be seen as a linked data that form a structured pattern. This feature supports information searching with semantic value. The ontology of Ulos Batak Toba has been developed by using Web Ontology Language (OWL), which is a vocabulary extension of the Resource Descriptive Framework (RDF). Then for the data retrieving process we use SPARQL</em></p><p class="Abstrak"> </p>
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Quinde, Cristina Páez, Efrén R. Narváez Peña, Margarita Narváez Ríos, Fernanda Viteri Toro, Francisco Torres Oñate, and Ruth Infante Paredes. "Designing an Ontology to Describe Ecological Cycling Routes within the Province of Tungurahua." Academic Research Community publication 2, no. 2 (May 27, 2018): 7. http://dx.doi.org/10.21625/archive.v2i2.250.
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Tourism, a significant industry worldwide, has allowed for economic, social, and cultural development in rural areas because of all the advantages it offers to tourists. Ecuador is a country that presents a wide range of alternatives in the tourist field allowing a massive tourist influx to many of its destinations such as indigenous communities, natural reserves, and tourist, ecological, and volcanic routes. Most importantly, Ecuador encourages the conservation of the diversity resulting from such influx. The objective of this research is to design an ontology which facilitates a description of the bicycle tourist routes in the province of Tungurahua, and specifically in the city of Ambato. Apart from route descriptions, this ontology gives information about the flora and fauna and places of interest such as inns, hotels, and restaurants that can be found along this route. This ontology was developed based on the application and enforcement of semantic web technologies. That being said, all the described information is attached to an RDF vocabulary and it can be accessed using SPARQL. Therefore, information that is semantically described in an organized and standardized manner is available in order to allow for interoperability with other existing data sources. As for the development of the ontology, the methodology used was an open code software known as “protégé”. The OWL (Ontology Web Language) was also used as marked language and RDFS for the description of the employed vocabulary.
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EUZENAT, JÉRÔME, JÉRÔME PIERSON, and FANO RAMPARANY. "Dynamic context management for pervasive applications." Knowledge Engineering Review 23, no. 1 (March 2008): 21–49. http://dx.doi.org/10.1017/s0269888907001269.
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AbstractPervasive computing aims at providing services for human beings that interact with their environment (encompassing objects and people who reside in it). Pervasive computing applications must be able to take into account the context in which users evolve, for example, physical location, social or hierarchical position, current tasks as well as related information. These applications have to deal with the dynamic integration in the environment of new, and sometimes unexpected, elements (users or devices). In turn, the environment has to provide context information to newly designed applications. This requires a framework which is open, dynamic and minimal. We describe an architecture in which context information is distributed in the environment and context managers use semantic Web technologies in order to identify and characterize available resources. The components in the environment maintain their own context expressed in RDF (Resource Description Framework) and described through OWL ontologies. They may communicate this information to other components, obeying a simple protocol for identifying them and determining the information they can provide. We show how this architecture allows introducing new devices and new applications without interrupting what is working. In particular, the openness of ontology description languages makes possible the extension of context descriptions and ontology matching helps dealing with independently developed ontologies.
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Nogales, Alberto, Miguel Angel Sicilia-Urban, and Elena García-Barriocanal. "Measuring vocabulary use in the Linked Data Cloud." Online Information Review 41, no. 2 (April 10, 2017): 252–71. http://dx.doi.org/10.1108/oir-06-2015-0183.
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Purpose This paper reports on a quantitative study of data gathered from the Linked Open Vocabularies (LOV) catalogue, including the use of network analysis and metrics. The purpose of this paper is to gain insights into the structure of LOV and the use of vocabularies in the Web of Data. It is important to note that not all the vocabularies in it are registered in LOV. Given the de-centralised and collaborative nature of the use and adoption of these vocabularies, the results of the study can be used to identify emergent important vocabularies that are shaping the Web of Data. Design/methodology/approach The methodology is based on an analytical approach to a data set that captures a complete snapshot of the LOV catalogue dated April 2014. An initial analysis of the data is presented in order to obtain insights into the characteristics of the vocabularies found in LOV. This is followed by an analysis of the use of Vocabulary of a Friend properties that describe relations among vocabularies. Finally, the study is complemented with an analysis of the usage of the different vocabularies, and concludes by proposing a number of metrics. Findings The most relevant insight is that unsurprisingly the vocabularies with more presence are those used to model Semantic Web data, such as Resource Description Framework, RDF Schema and OWL, as well as broadly used standards as Simple Knowledge Organization System, DCTERMS and DCE. It was also discovered that the most used language is English and the vocabularies are not considered to be highly specialised in a field. Also, there is not a dominant scope of the vocabularies. Regarding the structural analysis, it is concluded that LOV is a heterogeneous network. Originality/value The paper provides an empirical analysis of the structure of LOV and the relations between its vocabularies, together with some metrics that may be of help to determine the important vocabularies from a practical perspective. The results are of interest for a better understanding of the evolution and dynamics of the Web of Data, and for applications that attempt to retrieve data in the Linked Data Cloud. These applications can benefit from the insights into the important vocabularies to be supported and the value added when mapping between and using the vocabularies.
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"Policy based Security Framework in Semantic Web." International Journal of Engineering and Advanced Technology 9, no. 4 (April 30, 2020): 1606–13. http://dx.doi.org/10.35940/ijeat.d8697.049420.
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Semantic Web (SW), an extension of Web2.0 which can integrate various application and system such that data can be processed by machine instead of human using RDF, SPARQL, OWL technologies. With the passage of time advancement made in technologies which can provide dynamic support and interactions such as DAMLS [13], RDF AND RDFS, OWL, SWRL.As we are shifting towards making a system which is user interaction free, meet new security challenges [14]. Security is becoming prime important and a crucial factor in making an autonomous system, who will able to provide dynamic support and interaction of various clients and agents on a large scale? Success of Semantic Web depends on the way security is handle at various layers. Here, we are providing a policy based security framework containing Knowledge base, Distributed policy Management. Moreover, we have also provided a table with key points of SW and problem addressed in each research article.
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"Role of SPARQL in Leveraging Sematic Web Technology." International Journal of Engineering and Advanced Technology 9, no. 3 (February 29, 2020): 26–30. http://dx.doi.org/10.35940/ijeat.c5161.029320.
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Semantic web is not just a matter of translation from HTML to RDF/OWL languages. It is a matter of understanding the content of the web through knowledge graphs. Entities need to be related with relationships. This content is composed of resources (web pages) that contain, for example, text, images and audio. Thus, there is the need of extracting entities from these resources. Currently, most of the web content is in HTML5 format which is a W3C recommendation which enables describing the structure marginally with the help of annotations. The main challenge here is to transform unstructured data from plain HTML files to structured data (e.g RDF or OWL). The current work provides the first hand information for dealing with unstructured heterogeneous data residing on web using Twinkle, a Java tool for SPARQL query execution on FOAF (Friend Of A Friend) document.
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DUY CÔNG CHIẾN, TẠ. "AN APPROACH TO EXTENDING QUERY SENTENCE FOR SEMANTIC ORIENTED SEARCH ON KNOWLEDGE GRAPH." Journal of Science and Technology - IUH 50, no. 02 (August 2, 2021). http://dx.doi.org/10.46242/jst-iuh.v50i08.980.
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There are many applications related to semantic web, information retrieval, information extraction, and question answering applying ontologies in recent years. To avoid the conceptual and terminological confusion, an ontology is built as a taxonomy ontology which identifies and distinguishes concepts as well as terminology. It accomplishes this by specifying a set of generic concepts that characterizes the domain as well as their definitions and interrelationships. There are some methods to represent ontologies, such as Resource Description Framework (RDF), Web Ontology Language (OWL), databases etc. depending on the characteristic of data. RDF, OWL usually is used the cases when data structure is objects which the relationship among the objects is simple. But if the relationship among the objects is more complex, using databases for storing ontologies is an approach to be better. However, using relational databases do not sufficiently support the semantic orientated search by Structured Query Language (SQL) and the searching speed is slow. Therefore, this paper introduces an approach to extending query sentences for semantic oriented search on knowledge graph.
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Giunti, Marco, Giuseppe Sergioli, Giuliano Vivanet, and Simone Pinna. "Representing n-ary relations in the Semantic Web." Logic Journal of the IGPL, November 18, 2019. http://dx.doi.org/10.1093/jigpal/jzz047.
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Abstract Knowledge representation is a central issue for Artificial Intelligence and the Semantic Web. In particular, the problem of representing n-ary relations in RDF-based languages such as RDFS or OWL by no means is an obvious one. With respect to previous attempts, we show why the solutions proposed by the well known W3C Working Group Note on n-ary relations are not satisfactory on several scores. We then present our abstract model for representing n-ary relations as directed labeled graphs, and we show how this model gives rise to a new ontological pattern (parametric pattern) for the representation of such relations in the Semantic Web. To this end, we define PROL (Parametric Relational Ontology Language). PROL is an ontological language designed to express any n-ary fact as a parametric pattern, which turns out to be a special RDF graph. The vocabulary of PROL is defined by a simple RDFS ontology. We argue that the parametric pattern may be particularly beneficial in the context of the Semantic Web, in virtue of its high expressive power, technical simplicity, and faithful meaning rendition. Examples are also provided.
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"Semantic Web in the expansion of E Commerce." International Journal of Recent Technology and Engineering 8, no. 3 (September 30, 2019): 3820–27. http://dx.doi.org/10.35940/ijrte.c5078.098319.
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This study focuses on the enhancing the potential of the e-commerce websites with various Semantic web technologies. The involvement of semantic enrichment gives more meaning to the data and makes content more easily discoverable by both search engines and users. Daily thousands of people try searching for a product they are willing to buy and due to the system inefficiency, customers waste a lot of their precious time and resources and also there are a lot of problems with the current e-commerce systems. So, semantic web has certain technologies/languages specifically established for data, i.e. RDF (Resource description framework), OWL (Web ontology language) and XML, etc. which can help overcome the problems and accelerate the business to a higher level where e-commerce websites will be playing an important role.
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De Luca, Ernesto William, and Ingetraut Dahlberg. "Die Multilingual Lexical Linked Data Cloud: Eine mögliche Zugangsoptimierung?" Information - Wissenschaft & Praxis 65, no. 4-5 (September 1, 2014). http://dx.doi.org/10.1515/iwp-2014-0040.
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Sehr viele Informationen sind bereits im Web verfügbar oder können aus isolierten strukturierten Datenspeichern wie Informationssystemen und sozialen Netzwerken gewonnen werden. Datenintegration durch Nachbearbeitung oder durch Suchmechanismen (z. B. D2R) ist deshalb wichtig, um Informationen allgemein verwendbar zu machen. Semantische Technologien ermöglichen die Verwendung definierter Verbindungen (typisierter Links), durch die ihre Beziehungen zueinander festgehalten werden, was Vorteile für jede Anwendung bietet, die das in Daten enthaltene Wissen wieder verwenden kann. Um eine semantische Daten-Landkarte herzustellen, benötigen wir Wissen über die einzelnen Daten und ihre Beziehung zu anderen Daten. Dieser Beitrag stellt unsere Arbeit zur Benutzung von Lexical Linked Data (LLD) durch ein Meta-Modell vor, das alle Ressourcen enthält und zudem die Möglichkeit bietet sie unter unterschiedlichen Gesichtspunkten aufzufinden. Wir verbinden damit bestehende Arbeiten über Wissensgebiete (basierend auf der Information Coding Classification) mit der Multilingual Lexical Linked Data Cloud (basierend auf der RDF/OWL-Repräsentation von EuroWordNet und den ähnlichen integrierten lexikalischen Ressourcen MultiWordNet, MEMODATA und die Hamburg Metapher DB).
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Brandizi, Marco, Ajit Singh, Christopher Rawlings, and Keywan Hassani-Pak. "Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach." Journal of Integrative Bioinformatics 15, no. 3 (August 7, 2018). http://dx.doi.org/10.1515/jib-2018-0023.
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Abstract The speed and accuracy of new scientific discoveries – be it by humans or artificial intelligence – depends on the quality of the underlying data and on the technology to connect, search and share the data efficiently. In recent years, we have seen the rise of graph databases and semi-formal data models such as knowledge graphs to facilitate software approaches to scientific discovery. These approaches extend work based on formalised models, such as the Semantic Web. In this paper, we present our developments to connect, search and share data about genome-scale knowledge networks (GSKN). We have developed a simple application ontology based on OWL/RDF with mappings to standard schemas. We are employing the ontology to power data access services like resolvable URIs, SPARQL endpoints, JSON-LD web APIs and Neo4j-based knowledge graphs. We demonstrate how the proposed ontology and graph databases considerably improve search and access to interoperable and reusable biological knowledge (i.e. the FAIRness data principles).
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"An Ontology Based Expert System for Lung Cancer : OBESLC." International Journal of Engineering and Advanced Technology 9, no. 2 (December 30, 2019): 4622–26. http://dx.doi.org/10.35940/ijeat.b5116.129219.
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Lung Cancer is the second most recurrent cancer in both men and women and which is the leading cause of cancer death worldwide. The American cancer Society (ACS) in US estimates nearly 228,150 new cases of lung cancer and 142,670 deaths from lung cancer for the year 2019. This paper proposes to build an ontology based expert system to diagnose Lung Cancer Disease and to identify the stage of Lung Cancer. Ontology is defined as a specification of conceptualization and describes knowledge about any domain in the form of concepts and relationships among them. It is a framework for representing shareable and reusable knowledge across a domain. The advantage of using ontology for knowledge representation of a particular domain is they are machine readable. We designed a System named OBESLC (Ontology Based Expert System for Lung Cancer) for lung cancer diagnosis, in that to construct an ontology we make use of Ontology Web Language (OWL) and Resource Description Framework (RDF) .The design of this system depends on knowledge about patient’s symptoms and the state of lung nodules to build knowledge base of Lung Cancer Disease. We verified our ontology OBESLC by querying it using SPARQL query language, a popular query language for extracting required information from Semantic web. We validate our ontology by developing reasoning rules using semantic Web Rule Language (SWRL).To provide the user interface, we implemented our approach in java using Jena API and Eclipse Editor.
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Ageed, Zainab Salih, Rowaida Khalil Ibrahim, and Mohammed A. M. Sadeeq. "Unified Ontology Implementation of Cloud Computing for Distributed Systems." Current Journal of Applied Science and Technology, November 11, 2020, 82–97. http://dx.doi.org/10.9734/cjast/2020/v39i3431039.
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The ability to provide massive data storage, applications, platforms plus many other services leads to make the number of clouds services providers been increased. Providing different types of services and resources by various providers implies to get a high level of complexity. This complexity leads to face many challenges related to security, reliability, discovery, service selection, and interoperability. In this review, we focus on the use of many technologies and methods for utilizing the semantic web and ontology in cloud computing and distributed system as a solution for these challenges. Cloud computing does not have an own search engine to satisfy the needs of the providers of the cloud service. Using ontology enhances the cloud computing self-motivated via an intelligent framework of SaaS and consolidating the security by providing resources access control. The use RDF and OWL semantic technologies in the modeling of a multi-agent system are very effective in increases coordination the interoperability. One of the most efficient proposed frameworks is building cloud computing marketplace that collects the consumer's requirements of cloud services provider and managing these needs and resources to provide quick and reliable services.