Combining the Semantic Web with the Web as Background Knowledge for Ontology Mapping

2007 ◽  
pp. 814-831 ◽  
Author(s):  
Ruben Vazquez ◽  
Nik Swoboda
Keyword(s):  
Semantic Web ◽  
Background Knowledge ◽  
Ontology Mapping ◽  
The Web

scholarly journals Ontology mapping: the state of the art

2003 ◽  
Vol 18 (1) ◽  
pp. 1-31 ◽  
Author(s):  
YANNIS KALFOGLOU ◽  
MARCO SCHORLEMMER
Keyword(s):  
Semantic Web ◽  
Theoretical Approach ◽  
State Of The Art ◽  
The State ◽  
Ontology Mapping ◽  
Distributed Environment ◽  
Diverse Communities ◽  
Exchange Information ◽  
Multiple Ontologies ◽  
The Web

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mappings has been the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping.

SEMANTIC INTEROPERABILITY AND INFORMATION FLUIDITY

2006 ◽  
Vol 15 (01) ◽  
pp. 1-21 ◽  
Author(s):  
GUOFEI JIANG ◽  
GEORGE CYBENKO ◽  
JAMES A. HENDLER
Keyword(s):  
Semantic Web ◽  
Large Scale ◽  
Small World ◽  
Semantic Interoperability ◽  
Ontology Mapping ◽  
Semantic Mapping ◽  
Significant Information ◽  
Heterogeneous Information ◽  
Data Semantics ◽  
The Web

Ontologies are developed to describe data semantics on the Semantic Web. Given the distributed nature and scale of the Semantic Web, a large number of ontologies with different terminologies and structures will be created to describe the same concepts and domains. Without semantic mapping, information fluidity within the Web could be blocked at the boundaries of these ontologies. Therefore, ontology mapping is needed to translate datasets represented by disparate ontologies. We believe that over time communities will incrementally build an ontology mapping between select ontologies based on their own communication interests. How will these interest-driven mapping activities eventually change semantic interoperability and information fluidity across the Web? This paper proposes metrics to quantify information fluidity and builds an analytical model with "small-world" graph theory to analyze the growth of the Semantic Web. Further with this model, we analyze how information fluidity can evolve by "market-driven" semantic mapping activities occurring across the Web. Our results can be useful in evaluating mapping efforts needed for large-scale heterogeneous information systems. One conclusion, based on this model, is that the development of decentralized ontology mappings can lead to significant information fluidity within the Semantic Web.

Understanding Semantic Web: a conceptual model

2015 ◽  
Vol 64 (1/2) ◽  
pp. 82-100 ◽  
Author(s):  
Michael Calaresu ◽  
Ali Shiri
Keyword(s):  
Semantic Web ◽  
Conceptual Model ◽  
The Body ◽  
Three Dimensional Model ◽  
Conceptual Approach ◽  
Web Based ◽  
Content Type ◽  
Software Applications ◽  
Web Architecture ◽  
The Web

Purpose – The purpose of this article is to explore and conceptualize the Semantic Web as a term that has been widely mentioned in the literature of library and information science. More specifically, its aim is to shed light on the evolution of the Web and to highlight a previously proposed means of attempting to improve automated manipulation of Web-based data in the context of a rapidly expanding base of both users and digital content. Design/methodology/approach – The conceptual analysis presented in this paper adopts a three-dimensional model for the discussion of Semantic Web. The first dimension focuses on Semantic Web’s basic nature, purpose and history, as well as the current state and limitations of modern search systems and related software agents. The second dimension focuses on critical knowledge structures such as taxonomies, thesauri and ontologies which are understood as fundamental elements in the creation of a Semantic Web architecture. In the third dimension, an alternative conceptual model is proposed, one, which unlike more commonly prevalent Semantic Web models, offers a greater emphasis on describing the proposed structure from an interpretive viewpoint, rather than a technical one. This paper adopts an interpretive, historical and conceptual approach to the notion of the Semantic Web by reviewing the literature and by analyzing the developments associated with the Web over the past three decades. It proposes a simplified conceptual model for easy understanding. Findings – The paper provides a conceptual model of the Semantic Web that encompasses four key strata, namely, the body of human users, the body of software applications facilitating creation and consumption of documents, the body of documents themselves and a proposed layer that would improve automated manipulation of Web-based data by the software applications. Research limitations/implications – This paper will facilitate a better conceptual understanding of the Semantic Web, and thereby contribute, in a small way, to the larger body of discourse surrounding it. The conceptual model will provide a reference point for education and research purposes. Originality/value – This paper provides an original analysis of both conceptual and technical aspects of Semantic Web. The proposed conceptual model provides a new perspective on this subject.

A QoS-aware approach for runtime discovery, selection and composition of semantic web services

2016 ◽  
Vol 12 (2) ◽  
pp. 177-200 ◽  
Author(s):  
Sanjay Garg ◽  
Kirit Modi ◽  
Sanjay Chaudhary
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
User Satisfaction ◽  
Service Discovery ◽  
Semantic Web Services ◽  
Functional Requirements ◽  
Semantic Description ◽  
Content Type ◽  
The Web

Purpose Web services play vital role in the development of emerging technologies such as Cloud computing and Internet of Things. Although, there is a close relationship among the discovery, selection and composition tasks of Web services, research community has treated these challenges at individual level rather to focus on them collectively for developing efficient solution, which is the purpose of this work. This paper aims to propose an approach to integrate the service discovery, selection and composition of Semantic Web services on runtime basis. Design/methodology/approach The proposed approach defined as a quality of service (QoS)-aware approach is based on QoS model to perform discovery, selection and composition tasks at runtime to enhance the user satisfaction and quality guarantee by incorporating non-functional parameters such as response time and throughput with the Web services and user request. In this paper, the proposed approach is based on ontology for semantic description of Web services, which provides interoperability and automation in the Web services tasks. Findings This work proposed an integrated framework of Web service discovery, selection and composition which supports end user to search, select and compose the Web services at runtime using semantic description and non-functional requirements. The proposed approach is evaluated by various data sets from the Web Service Challenge 2009 (WSC-2009) to show the efficiency of this work. A use case scenario of Healthcare Information System is implemented using proposed work to demonstrate the usability and requirement the proposed approach. Originality/value The main contribution of this paper is to develop an integrated approach of Semantic Web services discovery, selection and composition by using the non-functional requirements.

scholarly journals A REVIEW ON SEMANTIC WEB

2020 ◽  
Vol 6 (12) ◽  
pp. 22-28
Author(s):  
Komal Dhulekar ◽  
Madhuri Devrankar
Keyword(s):  
Semantic Web ◽  
Modeling Languages ◽  
Technological Basis ◽  
Topic Maps ◽  
Cross Domain ◽  
Meta Information ◽  
Ontology Languages ◽  
Description Framework ◽  
Machine Processing ◽  
The Web

Semantic web is a concept that enables better machine processing of information on the web, by structuring documents written for the web in such a way that they become understandable by machines. This can be used for creating more complex applications (intelligent browsers, more advanced web agents), etc. Semantic modeling languages like the Resource Description Framework (RDF) and topic maps employ XML syntax to achieve this objective. New tools exploit cross domain vocabularies to automatically extract and relate the meta information in a new context. Web Ontology languages like DAML+OIL extend RDF with richer modeling primitives and a provide a technological basis to enable the Semantic Web. The logic languages for Semantic Web are described (which build on the of RDF and ontology languages). They, together with digital signatures, enable a web of trust, which will have levels of trust for its resources and for the rights of access, and will enable generating proofs, for the actions and resources on the web.

The Semantic Web and Its Entanglements

2017 ◽  
Vol 22 (1) ◽  
pp. 21-37 ◽  
Author(s):  
Matthew T. Mccarthy
Keyword(s):  
Artificial Intelligence ◽  
Semantic Web ◽  
Linked Data ◽  
Practice Theory ◽  
Knowledge Systems ◽  
Access To Information ◽  
Assemblage Theory ◽  
Complex Interactions ◽  
The World ◽  
The Web

The web of linked data, otherwise known as the semantic web, is a system in which information is structured and interlinked to provide meaningful content to artificial intelligence (AI) algorithms. As the complex interactions between digital personae and these algorithms mediate access to information, it becomes necessary to understand how these classification and knowledge systems are developed. What are the processes by which those systems come to represent the world, and how are the controversies that arise in their creation, overcome? As a global form, the semantic web is an assemblage of many interlinked classification and knowledge systems, which are themselves assemblages. Through the perspectives of global assemblage theory, critical code studies and practice theory, I analyse netnographic data of one such assemblage. Schema.org is but one component of the larger global assemblage of the semantic web, and as such is an emergent articulation of different knowledges, interests and networks of actors. This articulation comes together to tame the profusion of things, seeking stability in representation, but in the process, it faces and produces more instability. Furthermore, this production of instability contributes to the emergence of new assemblages that have similar aims.

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