Integrating Databases into the Semantic Web through an Ontology-Based Framework

The Web, as we know it, is a collection of human readable pages that are virtually unintelligible to computer programs. For that reason, it has been called the “eyeball” Web. While the Web emerged as a World Wide repository of digitized information, by and large, the very same information is not available for automatic computation. In recent years two parallel efforts emerged that have the potential of overcoming this paradox: the first effort is the Semantic Web which provides the tools for the explicit markup of the content of Web pages; the second effort is the development of Web Services which results in a Web where programs act as independent agents to become the producers and consumers of information and enable automation of business transactions.In this talk I will focus on research that attempts to bridge the gap between the Web as we know it, the Semantic Web and Web services. Under this approach, I propose the vision of Web services as autonomous goal-directed agents which select other agents to interact with, and flexibly negotiate their interaction model, acting at times in client server mode, or at other times in peer to peer mode. The resulting Web services, that I call Autonomous Semantic Web services, utilize ontologies and semantically annotated Web pages to automate the fulfillment of tasks and transactions with other Web agents. In particular, Autonomous Semantic Web services use the Semantic Web to support capability based discovery and interoperation at run time. A first step towards this vision is the development of formal languages and inference mechanisms for representing and reasoning with core concepts of Web services. DAML-S (the Darpa Agent Markup Language for Services) is the first attempt to define such a language. I will give a brief overview of DAML-S and its relations with the Semantic Web and Web services. In addition, I will provide concrete examples of computational models of how DAML-S can be viewed as the first step in bridging the gap between the Semantic Web and current proposed industry standards for Web services. I will provide concrete examples of DAML-S in action, discuss challenges still open in the bridging between the Semantic Web and Web services and provide a roadmap to get us from today’s Web to the Web of autonomous Semantic Web services.KeywordsFormal LanguageCore ConceptDigitize InformationAutomatic ComputationBusiness TransactionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Semantic Web is the name of the next generation World Wide Web, that has been recently proposed by Tim Berners-Lee and the World Wide Web Consortium (W3C)1. In this new Web architecture, information and Web services will be easily understandable and usable by both humans and computers. The objective is not to make computers understand the human language, but to define a universal model for the expression of the information and a set of inference rules that machines can easily use in order to process and relate the information as if they really understood it (Berners-Lee, 1998). Though, as the current Web provided sharing of documents among previously incompatible computers, the Semantic Web intends to go beyond, allowing stovepipe systems, hardwired computers, and other devices to share contents embedded in different documents. The most known architecture for Semantic Web is based on a stack of related technologies, each one being a whole research area by itself (Berners-Lee, Hendler, & Lassila. 2001; Pereira & Freire, 2005). Accomplishment of the Semantic Web is considered a great challenge, not only due to the complexity of implementation but also because of the vast applicability in several areas. In spite of this, Semantic Web is still one of the most promising research areas among those which aim to define a new architecture for the Web. Semantic Web goes far beyond previous information retrieval and knowledge representation projects, presenting a non-centralized way to represent and contextualize real-world concepts, unambiguously, for several areas of knowledge. Semantic Web-enabled machines will handle information at our communication level. It is clear that the ability to interpret reality is still very primitive, however, Semantic Web points a way towards machine interaction and learning (Pereira et al., 2005). Semantic Web will integrate, interact with, and bring benefits to most human activities. Its full potential will go beyond the Web to real-world machines, providing increased interaction between machines and with humans—smarter phones, radios, and other electronic devices. Semantic Web will bring a different kind of approach in the understanding of reality by the machines and will constitute a mark in the evolution of human knowledge (Pereira et al., 2005).

Assessing the quality of sensor-originated information is key for the effective and predictable operation sensor-enabled computerized applications. However, with increasing uncertainties due to alternative deployment scenarios, operational realities, and sensing resource use, it becomes very challenging in designing replicable software solutions that can be easily reused in a number of occasions with minimal customization. Leveraging semantic sensor web technologies, this paper presents an ontology-based design framework for organizing a library of quality of information (QoI) analysis algorithms specific to a data source, and interfacing to a library containing computational algorithms assessing quality of information. The ontology-based framework is broad enough to allow easy accommodation of new computational algorithms that domain experts may provide to the library as needed to reflect specific deployment, operational, sensing realities.

Semantic Web services is considered as the concept bringing the web to its full potential by combining the best features of web services, agent technology, grid and the Semantic web. In this paper we present a semantic Web Services platform based on software agent (JASW), which introduces Semantic web and software agent and takes the automated discovery, selection, orchestration and invocation of Web services as application background. In the platform, we adopt Semantic web to accurately describe Web services, and use software agent to implement discovery, selection, and orchestration of Web services.

With the proliferation of very large data repositories hidden behind web interfaces, e.g., keyword search, form-like search and hierarchical/graph-based browsing interfaces for Amazon.com, eBay.com, etc., efficient ways of searching, exploring and/or mining such web data are of increasing importance.

Since archaeology in particular and humanities in general are interdisciplinary disciplines, there is an imperious need to enhance the accessibility and harmonise data integration, given their varied resource types (books, archives, scientific data, GIS, 3D models etc) and their different conceptual and technological structures and standards. A factor that further reduces accessibility and query performances is related to storing, such as physical location of data, language, and interface. The advent of Semantic Web technology represents an important advance in creating networks of archaeological knowledge based on various resources available on-line. While the valuable use of CIDOC-CRM (Comite International pour la Documentation -Conceptual Reference Model) ontology for specific CH (Cultural Heritage) domains (e.g. museums, libraries, etc) has been partially demonstrated, the interdisciplinary implementations are limited. In this article, we explore the potential of the CIDOC-CRM for a cross-domain implementation of CH data integration. We conducted tha mappings of different on-line resources related to Stonehenge to CIDOC-CRM, and evaluated them in the MAD database, a web-based application that manages natively XML-based datasets. The result ensures the validity of mapping mechanism and the semantic integration of CH data from different sources.

Exploiting tourism destinations’ knowledge in an RDF-based P2P network

Semantic Web for Health Care and Life Sciences: a review of the state of the art

CiteSeer is currently a very large source of meta-data information on the World Wide Web (WWW). This meta-data is the key material for the Semantic Web. Still, CiteSeer is not yet a Semantic-enabled service and therefore its meta-data, although potentially usable by Semantic Web agents, is not yet reachable using the Semantic Web mechanisms. The complexity of CiteSeer, that is the range of tasks it supports, make the transition to a Semantic-enabled service a non-trivial task. While human users tend to perceive CiteSeer as a single well-integrated service, we believe it is best seen - from a machine perspective - as a collection of services, each service performing a specific task. In this paper we show our approach to enable CiteSeer on the Semantic Web in order to allow the use of its meta-data through the Semantic Web. We first introduce an intuitive Application Programming Interface (API) to the CiteSeer software, then show that an efficient integration of CiteSeer in the Semantic Web can be best achieved by independently integrating the services that comprise it. We believe the effort presented here towards the Semantic-integration of a complex Information Retrieval system could be used as an integration model for arbitrary systems.

Intelligent, autonomous agents are still not available in the Semantic Web at large scale today. Also the fields of Semantic Web and Multi-Agent Systems are not working together very closely although they could profit much from each other. Existing approaches merely use the Web as a transport layer and are not properly aligned to the architectural style of the Web. The Internet of Things, which would be very useful for agents to act upon Things in the real world, on the other side is very fragmented and not easily inter-operable. The Web of Things has emerged as an approach to use the (Semantic) Web as an application layer for Things. It is still unclear however, how agents on the WoT should look like. We propose that the Semantic Web is a suitable integration layer, both for agents and Things. We investigate how a Multi-Agent System in the Semantic Web of Things can be build by utilizing simple reflex agents and the communication paradigm of stigmergy. We map Things and artifacts to Web resources that are managed by a Web server and provide affordances to agents through hypermedia.KeywordsMulti-Agent SystemsWeb of ThingsSimple reflex agentsStigmergyRestHypermedia

This paper presents a systematic literature review of research focused on use of Semantic Web technologies in formal educational contexts. Through systematic search, the review has identified 199 research articles, which are examined with the intention of identifying prevalent themes within the body of research within the field of formal educational use of Semantic Web technologies. The themes identified by the review are: (1) Semantic Web ontologies; (2) Efficient distribution, accessibility, retrieval, reuse and combination of educational resources; (3) Linked Data; (4) Semantic Web enhanced virtual learning environments and personalization of learning environments; (5) Semantic Web learning objects; (6) Evaluation, feedback and assessment; (7) Semantic Web services; (8) Pedagogical tools for teachers and students. Furthermore, this review seeks to examine how these themes and the use of Semantic Web technologies in formal education reflects on the ongoing discussion of how pedagogy and technology should interact. The outset of this discussion is a previous study by Dirckinck‐Holmfeld, which establishes that there is a tendency to emphasize technology over pedagogy in educational design and development.

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

The role of the Semantic Web in Web 3.0, the next evolution of the internet, is significant. Web 3.0 is often referred to as the ‘intelligent web’ or the ‘Semantic Web’. The Semantic Web is an essential topic in Web 3.0 because it enables data integration, enhances data search on the World Wide Web, and promotes the development of knowledge graphs that allow computers to derive new insights and generate knowledge. Teaching the Semantic Web to undergraduate students offers numerous benefits. Students gain a deep understanding of cutting-edge web technologies, technical skills in data integration (the ability to develop systems with diverse datasets and linked data), and capabilities in information retrieval and knowledge management (data modelling and linked data querying). Moreover, they are able to design and develop different types of web-based applications such as intelligent data-driven decision-making apps, AI apps, or personalised-recommendation apps. In this article, we present ways to effectively integrate the Semantic Web as a subject in the current Computing Systems curriculum offering at Eastern Institute of Technology (EIT). We also propose a recommended list of theory topics, practical labs and practical projects that should be designed and developed to teach this paper effectively for undergraduate students.

EUROLAN, which has been held biennially since 1993, is one of the most significant European summer schools in the area of natural language processing. Each of the EUROLAN sessions has focused on an area of timely interest to researchers in the field; this year's EUROLAN involved students in tutorials and hands-on sessions concerned with semantic web technologies as applied to language processing, ontology creation and use, and consideration of the semantic web's potential and limitations.

Standards for image annotation using Semantic Web