Applying Semantic Linkage in the Geospatial Web

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

Semantic mashup of biomedical data

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.

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

Chapter 10 Ontology-based Multi-source Data Integration for Digital Soil Mapping

In this paper we explore some of the opportunities and challenges for machine learning on the Semantic Web. The Semantic Web provides standardized formats for the representation of both data and ontological background knowledge. Semantic Web standards are used to describe meta data but also have great potential as a general data format for data communication and data integration. Within a broad range of possible applications machine learning will play an increasingly important role: Machine learning solutions have been developed to support the management of ontologies, for the semi-automatic annotation of unstructured data, and to integrate semantic information into web mining. Machine learning will increasingly be employed to analyze distributed data sources described in Semantic Web formats and to support approximate Semantic Web reasoning and querying. In this paper we discuss existing and future applications of machine learning on the Semantic Web with a strong focus on learning algorithms that are suitable for the relational character of the Semantic Web's data structure. We discuss some of the particular aspects of learning that we expect will be of relevance for the Semantic Web such as scalability, missing and contradicting data, and the potential to integrate ontological background knowledge. In addition we review some of the work on the learning of ontologies and on the population of ontologies, mostly in the context of textual data.

Semantic Web Services are the key technology providing services for the users' convenience in the semantic web environment. Many companies in various fields are researching and developing languages for constructing Semantic Web Services such as DAML-S, WSDL, X-LANG and BPEL4WS. DAML-S is a method that accesses the existing Web Service method from a semantic web environment. However, the current Semantic Web Services Discovery System does not provide sufficient processing of quality factors (performance, accessibility, availability, reliability and transaction) nor reliable and accurate service results desired by the user through a UDDi search method. The present study analyzes the disadvantages of the current web services and suggests a Semantic Web Services Discovery System based on QoS applying semantic web technologies as a solution to the problems. The suggested system provides a UDDi and DAML-S based discovery engine to allow efficient web service discovery and composition.

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.

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).

In this paper, we proposed a semantic integration framework of heterogeneous data based on domain ontology construction. The mechanism of domain ontology construction and mapping for heterogeneous data are studied, the purposes of which are to enhance the capability of dynamic adaptability and optimization of domain ontology construction, to resolve the problems of data heterogeneity in the processing of semantic information integration, and to promote the flexibility of the semantic integration process. Next, as to the semantic query, the theory and methods of specification or dynamic expansion of semantic query based on social annotation and ontology, and the duplicate removal and aggregating optimization of semantic query results are explored, the purpose of which is to realize the usability of semantic integration system and the credibility of the query results. Finally, an experimental prototype system of semantic integration of oil and gas exploration data based on domain ontology construction is constructed, the purpose of which is to verify the feasibility and correctness of the proposed theories and methods.KeywordsSemantic integrationOntology constructionDomain ontology

Efficiently finding Web Services on the Web is a challenge research question in Service Oriented Architecture-SOA. Web services are becoming necessary part of the Semantic Web, and research on Semantic Web Services aims to automate their use. However, finding the adequate service for each individual user becomes a more and more demanding problem. In this paper we suggest a new approach for Web Service Discovery which we believe that is the first attempts that combines clustring techiques with Latent Semantic Indexing. Empirically the proposed method will improve the quality of automated service discovery.

The Semantic Web offers significant capabilities that transform the current Web into a global knowledge base including various cross-linked multimedia content with formal descriptions of its semantics understandable to humans and processable by computers. Content on the Semantic Web can be subject to reasoning and queries with standardized languages, methods and tools, which opens new opportunities for collaborative creation, use and exploration of web repositories. However, these opportunities have not been exploited so far by the available 3D formats and modeling tools, which limits the possibilities of search and reuse of 3D content as part of the Semantic Web. This work contributes a semantic development pipeline of the X3D Ontology, with corresponding conversion of X3D models into triple forms suitable for formal query. The ontology design reflects experience accompanying the development of the Extensible 3D (X3D) Graphics International Standard, in particular, the X3D Unified Object Model (X3DUOM). This approach combines semantic and syntactic elements of X3D models and metadata to support integration with the Semantic Web. The pipeline enables automatic generation of the X3D Ontology, thereby providing an up-to-date 3D representation with semantics during X3D specification development. By extending commonplace model conversions from other formats to X3D, the ontology presents the potential to enable integration of most forms of 3D content with the Semantic Web.

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.

The vision of the Semantic Web is to reduce manual discovery and usage of Web resources (documents and services) and to allow software agents to automatically identify these Web resources, integrate them and execute them for achieving the intended goals of the user. Such a composed Web service may be represented as a workflow, called service flow. Current studies of Web services are not sufficient for automatic composition. This paper presents different types of compositional knowledge required for Web service discovery and composition: syntactic, semantic and pragmatic knowledge. As a proof of concept, we have implemented our framework in a cardiovascular domain which requires advanced service discovery and composition across heterogeneous platforms of multiple organizations. Within this framework, we describe (1) How to represent the compositional knowledge, which plays a role in service discovery and composition, in DAML-S; (2) How heterogeneous medical services intemperate in a composed medical service flow. (3) To solve this knowledge level integration, we build on an ontology integration method called SEMIO (Semantic Interoperability).

Web services – a new breed of self-contained, self-describing, modular applications published, located, and invoked across the Web – handle functions, from simple requests to complicated business processes. They are defined as network-based application components with a services-oriented architecture (SOA) using standard interface description languages and uniform communication protocols. SOA enables organizations to grasp and respond to changing trends and to adapt their business processes rapidly without major changes to the IT infrastructure. The Inaugural International Conference on Next-Generation Web Services Practices (NWeSP'05) attracted researchers who are also the world's most respected authorities on the semantic Web, Web-based services, and Web applications and services. NWeSP'05 was held in cooperation with the IEEE Computer Society Task Force on Electronic Commerce, the Technical Committee on Internet, and the Technical Committee on Scalable Computing. This special issue presents eight papers focused on different aspects of Web services and their applications. Papers were selected based on fundamental ideas and concepts rather than the thoroughness of techniques employed. Papers are organized as follows: <I>Taher et al.</I> present the first paper, on a Quality of Service Information and Computational framework (QoS-IC) supporting QoS-based service selection for SOA. The framework's functionality is expanded using a QoS constraints model that establishes an association relationship between different QoS properties and is used to govern QoS-based service selection in the underlying algorithm. Using a prototype implementation, the authors demonstrate how QoS constraints improve QoS-based service selection and save consumers valuable time. Due to the complex infrastructure of web applications, response times perceived by clients may be significantly longer than desired. To overcome some of the current problems, <I>Vilas et al.</I>, in the second paper, propose a cache-based extension of the architecture that enhances the current web services architecture, which is mainly based on program-logic or protocol-dependent optimization. In the third paper, Jo and Yoo present authorization for securing XML sources on the Web. One of the disadvantages of existing access control is that the DOM tree must be loaded into memory while all XML documents are parsed to generate the DOM tree, such that a lot of memory is used in repetitive search for tree to authorize access to all nodes in the DOM tree. The complex authorization evaluation process required thus lowers system performance. Existing access control fails to consider information structure and semantics sufficiently due to basic HTML limitations. The authors overcome some of these limitations in the proposed model. In the fourth paper, Jung and Cho propose a novel behavior-network-based method for Web service composition. The behavior network selects services automatically through internal and external links with environmental information from sensors and goals. An optimal service is selected at each step, resulting in a globally optimal service sequence for achieving preset goals. The authors detail experimental results for the proposed model by comparing them with rule-based system and user tests. <I>Kong et al.</I> present an efficient method in the fifth paper for merging heterogeneous ontologies – no ontology building standard currently exists – and the many ontology-building tools available are based on different ontology languages, mostly focusing on how to create, edit and infer the ontology efficiently. Even ontologies about the same domain differ because ontology experts hold different view points. For these reasons, interoperability between ontologies is very low. The authors propose merging heterogeneous domain ontologies by overcoming some of the above limitations. In the sixth paper, Chen and Che provide polynomial-time tree pattern query minimization algorithm whose efficiency stems from two key observations: (i) Inherent redundant "components" usually exist inside the rudimentary query provided by the user, and (ii) nonedundant nodes may become redundant when constraints such as co-occurrence and required child/descendant are given. They show that the algorithm obtained by first augmenting the input tree pattern using constraints, then applying minimization, invariably finds a unique minimal equivalent to the original query. Chen and Che present a polynomial-time algorithm for tree pattern query (TPQ) minimization without XML constraints in the seventh paper. The two-part algorithm is a dynamic programming strategy for finding all matching subtrees within a TPQ. The algorithm consists of one for subtree recognization and a second for subtree deletion. In the last paper, <I>Bagchi et al.</I> present the mobile distributed virtual memory (MDVM) concept and architecture for cellular networks containing server-groups (SG). They detail a two-round randomized distributed algorithm to elect a unique leader and co-leader of the SG that is free of any assumption about network topology, and buffer space limitations and is based on dynamically elected coordinators eliminating single points of failure. As guest editors, we thank all authors featured in this special issue for their contributions and the referees for critically evaluating the papers within the short time allotted. We sincerely believe that readers will share our enjoyment of this special issue and find the information it presents both timely and useful.