285 research outputs found
On the emergent Semantic Web and overlooked issues
The emergent Semantic Web, despite being in its infancy, has already received a lotof attention from academia and industry. This resulted in an abundance of prototype systems and discussion most of which are centred around the underlying infrastructure. However, when we critically review the work done to date we realise that there is little discussion with respect to the vision of the Semantic Web. In particular, there is an observed dearth of discussion on how to deliver knowledge sharing in an environment such as the Semantic Web in effective and efficient manners. There are a lot of overlooked issues, associated with agents and trust to hidden assumptions made with respect to knowledge representation and robust reasoning in a distributed environment. These issues could potentially hinder further development if not considered at the early stages of designing Semantic Web systems. In this perspectives paper, we aim to help engineers and practitioners of the Semantic Web by raising awareness of these issues
Optimizing Description Logic Reasoning for the Service Matchmaking and Composition
The Semantic Web is a recent initiative to expose semantically rich information associated with Web resources to build more intelligent Web-based systems. Recently, several projects have embraced this vision and there are several successful applications that combine the strengths of the Web and of semantic technologies. However, Semantic Web still lacks a technology, which would provide the needed scalability and integration with existing infrastructure. In this paper we present our ongoing work on a Semantic Web repository, which is capable of addressing complex schemas and answer queries over ontologies with large number of instances. We present the details of our approach and describe the underlying architecture of the system. We conclude with a performance evaluation, which compares the current state-of-the-art reasoners with our system
Semantic Network Analysis of Ontologies
A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies. We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size
Modeling views in the layered view model for XML using UML
In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction
Towards the new generation of web knowledge
Purpose - As the web evolves its purpose and nature of its use are changing. The purpose of the paper is to investigate whether the web can provide for the competing stakeholders, who are similarly evolving and who increasingly see it as a significant part of their business.
Design/methodology/approach - The paper adopts an exploratory and reviewing approach to the emerging trends and patterns emanating from the web's changing use and explores the underpinning technologies and tools that facilitate this use and access. It examines the future and potential of web-based knowledge management (KM) and reviews the emerging web trends, tools, and enabling technologies that will provide the infrastructure of the next generation web.
Findings - The research carried out provides an independent framework for the capturing, accessing and distributing of web knowledge. This framework retains the semantic mark-up, a feature that we deem indispensable for the future of KM, employing web ontologies to structure organisational knowledge and semantic text processing for the extraction of knowledge from web sites.
Practical implications - As a result it was possible to identify the implications of integrating the two aspects of web-based KM, namely the business-organisational-users' perspective and that of the enabling web technologies.
Originality/value - The proposed framework accommodates the collaborative tools and services offered by Web 2.0, acknowledging the fact that knowledge-based systems are shared, dynamic, evolving resources, whose underlying knowledge model requires careful management due to its constant changing
Semantic Content Mediation and Acquisition: The Challenge for Semantic e-Business Solutions
A Top Quadrant report situates the Semantic Web within the current Innovation Wave of âDistributed Intelligenceâ. This is one of the main innovation waves of the last centuries including textile, railway, auto, computer, distributed intelligence (1997-2061) and nanotechnology (2007-2081). The Distributed Intelligence wave started in the late nineties and is expected to peak between 2010 and 2020. The report estimates first return on investments in 2006-7, growing to a market of $40-60 billion in 2010. Funds are coming primary from governments, venture capitalists and industry commercialization. Over the next few years, this is expected to change in favour of industry commercialization
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