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Decentralized case-based reasoning (DzCBR) is a reasoning framework that addresses the problem of adaptive reasoning in a multi-ontology environment. It is a case-based reasoning (CBR) approach which relies on contextualized ontologies in the C-OWL formalism for the representation of domain knowledge and adaptation knowledge. A context in C-OWL is used to represent a particular viewpoint, containing the knowledge needed to solve a particular local problem. Semantic relations between contexts and the associated reasoning mechanisms allow the CBR process in a particular viewpoint to reuse and share information about the problem and the already found solutions in the other viewpoints. [ABSTRACT FROM AUTHOR]

Ontology tools performance and scalability are critical to both the growth of the Semantic Web and the establishment of these tools in the industry. In this paper, we present briefly the benchmarking methodology used to improve the performance and the scalability of ontology development tools. We focus on the definition of the infrastructure for evaluating the performance of these tools' ontology management APIs in terms of its execution efficiency. We also present the results of applying the methodology for evaluating the API of the WebODE ontology engineering workbench. [ABSTRACT FROM AUTHOR]

The semantic web presents the vision of a distributed, dynamically growing knowledge base founded on formal logic. Common users, however, seem to have problems even with the simplest Boolean expressions. As queries from web search engines show, the great majority of users simply do not use Boolean expressions. So how can we help users to query a web of logic that they do not seem to understand? We address this problem by presenting a natural language interface to semantic web querying. The interface allows formulating queries in Attempto Controlled English (ACE), a subset of natural English. Each ACE query is translated into a discourse representation structure - a variant of the language of first-order logic - that is then translated into an N3-based semantic web querying language using an ontology-based rewriting framework. As the validation shows, our approach offers great potential for bridging the gap between the logic-based semantic web and its real-world users, since it allows users to query the semantic web without having to learn an unfamiliar formal language. Furthermore, we found that users liked our approach and designed good queries resulting in a very good retrieval performance (100% precision and 90% recall). [ABSTRACT FROM AUTHOR]

This paper presents Oyster, a Peer-to-Peer system for exchanging ontology metadata among communities in the Semantic Web. We describe how Oyster assists researchers in re-using existing ontologies, and how Oyster exploits semantic web techniques in data representation, query formulation, query result presentation to provide an online solution to share ontologies. [ABSTRACT FROM AUTHOR]

CONFOTOhttp://www.confoto.org/ is a semantic browsing and annotation service for conference photos. It combines recent Web trends with the advantages of Semantic Web platforms. The service offers several tools to upload, link, browse and annotate pictures. Simple forms can be used to create multilingual titles, tags, or descriptions, while more advanced forms allow the relation of pictures to events, persons, ratings, and copyright information. CONFOTO provides tailored and interlinked browsers for photos, people, events, and documents. Remotely maintained photo descriptions can be added to the local knowledge base, data re-use is made possible via customizable syndication functions and a query interface. [ABSTRACT FROM AUTHOR]

It is tedious and error-prone to query search engines manually in order to accumulate a large body of factual information. Search engines retrieve and rank potentially relevant documents for human perusal, but do not extract facts, or fuse information from multiple documents. This paper introduces DynamicView, a Semantic Web application for researchers to query, browse and visualize distribution and evolution of research areas in computer science. Present and historical web pages of top 20 universities in USA and China are analyzed, and research areas of faculties in computer science are extracted automatically by segmentation based algorithm. Different ontologies of ACM and MST classification systems are combined by SKOS vocabularies, and the classification of research areas is learned from the ACM Digital Library. Query results including numbers of researchers and their locations are visualized in SVG map and animation. Interestingly, great differences of hot topics do exist between the two countries, and the number of researchers in certain areas changed greatly from the year 2000 to 2005. [ABSTRACT FROM AUTHOR]

Bioinformatics and genomics cover a wide range of different data formats (i.e. annotations, pathways, structures, sequences) derived from experimental and in-silico biological analysis which are stored, used, and manipulated by scientists and machines. The volume of this data is huge and usually distributed in different locations, and often frequently being updated. FungalWeb is the first project of its kind in Canada to focus on bringing semantic web technology to genomics. It aimed to bring together available expertise in ontologies, multi-agent systems, machine learning and natural language processing to build a tailored knowledgebase and semantic systems of direct use to the scientific discovery process in the domain of fungal genomics [1]. [ABSTRACT FROM AUTHOR]

This application demonstrates how to provide personalized, syndicated views on distributed web data using Semantic Web technologies. The application comprises four steps: The information gathering step, in which information from distributed, heterogenous sources is extracted and enriched with machine-readable semantics, the operation step for timely and up-to-date extractions, the reasoning step in which rules reason about the created semantic descriptions and additional knowledge-bases like ontologies and user profile information, and the user interface creation step in which the RDF-descriptions resulting from the reasoning step are interpreted and translated into an appropriate, personalized user interface. We have developed this application for solving the following real-world problem: We provide personalized, syndicated views on the publications of a large European research project with more than twenty geographically distributed partners and embed this information with contextual information on the project, its working groups, information about the authors, related publications, etc.This research has partially been supported by REWERSE - Reasoning on the Web (www.rewerse.net), Network of Excellence, 6th European Framework Program. Keywords: web data extraction, web data syndication, personalized views. [ABSTRACT FROM AUTHOR]

The Semantic Web is a difficult concept for typical end-users to comprehend. There is a lack of widespread understanding on how the Semantic Web could be used in day-to-day applications. While there are now practical applications that have appeared supporting back-end functions such as data integration, there is only a handful of Semantic Web applications that the average Google user would want to use on a regular basis. The Concept Object WebDemo available at http://semanticobjectweb.isx.com is a prototype application for knowledge/intelligence management that aggregates data from text documents, XML files, and databases so that end-users can visually discover and learn about knowledge object (entities) without reading documents. The application addresses limitations with current knowledge/intelligence management tools giving end-users the power of the Semantic Web without the perceived burden and complexity of the Semantic Web. [ABSTRACT FROM AUTHOR]

The integration of heterogenous data sources is a crucial step for the upcoming semantic web - if existing information is not integrated, where will the data come from that the semantic web builds on? In this paper we present the gnowsis adapter framework, an implementation of an RDF graph system that can be used to integrate structured data sources, together with a set of already implemented adapters that can be used in own applications or extended for new situations. We will give an overview of the architecture and implementation details together with a description of the common problems in this field and our solutions, leading to an outlook on the future developments we expect. Using our presented results, researchers can generate test data for experiments and practitioners can access their desktop data sources as RDF graph.This work was supported by the German Federal Ministry of Education, Science, Research and Technology (bmb+f), (Grant 01 IW C01, Project EPOS: Evolving Personal to Organizational Memories). [ABSTRACT FROM AUTHOR]

Besides the reduction of time to market, there may be observed another trend in the automotive industry: built-to-order. Built-to-order reduces the mass production of cars to a limited-lot-production. Emphasis for optimization issues moves then from the production step to earlier steps as the collaboration of suppliers and manufacturer in development and delivering. Thus knowledge has to be shared between different organizations and departments in early development processes. In this paper we describe a project in the automotive industry where ontologies have two main purposes: (i) representing and sharing knowledge to optimize business processes for the testing of cars and (ii) integration of life data into this optimization process. A test car configuration assistant (semantic guide) is built on top of an inference engine equipped with an ontology containing information about parts and configuration rules. The ontology is attached to the legacy systems of the manufacturer and thus accesses and integrates up-to-date information. This semantic guide accelerates the configuration of test cars and thus reduces time to market. [ABSTRACT FROM AUTHOR]

In this paper, we present a demonstrator system which applies semantic web services technology to business-to-business integration, focussing specifically on a logistics supply chain. The system is able to handle all stages of the service lifecycle - discovery, service selection and service execution. One unique feature of the system is its approach to protocol mediation, allowing a service requestor to dynamically modify the way it communicates with aprovider, based on a description of the provider's protocol. We present the architecture of the system, together with an overview of the key components (discovery and mediation) and the implementation. [ABSTRACT FROM AUTHOR]

The Royal Institute Elcano Juan Sebastián Elcano was a Spanish explorer, who commanded back home the first successful expedition to circumnavigate the globe in 1522. (Real Instituto Elcano) in Spain is a prestigious independent political institute whose mission is to comment on the political situation in the world focusing on its relation to Spain. As part of its dissemination strategy it operates a public website. In this paper we present and evaluate the application of a semantic search engine to improve access to the Institute's content: instead of retrieving documents based on user queries of keywords, the system accepts queries in natural language and returns answers rather than links to documents. Topics that will be discussed include ontology construction, automatic ontology population, semantic access through a natural language interface and a failure analysis. [ABSTRACT FROM AUTHOR]

Since mobile Internet services are rapidly proliferating, finding the most appropriate service or services from among the many offered requires profound knowledge about the services which is becoming virtually impossible for ordinary mobile users. We propose a system that assists non-expert mobile users in finding the appropriate services that solve the real-world problems encountered by the user. Key components are a task knowledge base of tasks that a mobile user performs in daily life and a service knowledge base of services that can be used to accomplish user tasks. We present the architecture of the proposed system including a knowledge modeling framework, and a detailed description of a prototype system. We also show preliminary user test results; they indicate that the system allows a user to find appropriate services quicker with fewer loads than conventional commercial methods. [ABSTRACT FROM AUTHOR]

Rule languages and rule systems are widely used in business applications including computer-aided training, diagnostic fact finding, compliance monitoring, and process control. However, there is little interoperability between current rule-based systems. Interoperation is one of the main goals of the Semantic Web, and developing a language for sharing rules is often seen as a key step in reaching this goal. The Semantic Web Rule Language (SWRL) is an important first step in defining such a rule language. This paper describes the development of a configurable interoperation environment for SWRL built in Protégé-OWL, the most widely-used OWL development platform. This environment supports both a highly-interactive, full-featured editor for SWRL and a plugin mechanism for integrating third party rule engines. We have integrated the popular Jess rule engine into this environment, thus providing one of the first steps on the path to rule integration on the Web. [ABSTRACT FROM AUTHOR]

The uptake of Semantic Web technology by industry is progressing slowly. One of the problems is that academia is not always aware of the concrete problems that arise in industry. Conversely, industry is not often well informed about the academic developments that can potentially meet its needs. In this paper we present a first step towards a successful transfer of knowledge-based technology from academia to industry. In particular, we present a collection of use cases from enterprises which are interested in Semantic Web technology. We provide a detailed analysis of the use cases, identify their technology locks, discuss the appropriateness of knowledge-based technology and possible solutions. We summarize industrial knowledge processing requirements in the form of a typology of knowledge processing tasks and a library of high level components for realizing those tasks. Eventually these results are intended to focus academia on the development of plausible knowledge-based solutions for concrete industrial problems, and therefore, facilitate the uptake of Semantic Web technology within industry. [ABSTRACT FROM AUTHOR]

Situation awareness involves the identification of relationships among objects participating in an evolving situation. This problem in general is intractable and thus requires additional constraints and guidance defined by the user if there is to be any hope of creating practical situation awareness systems. This paper describes a Situation Awareness Assistant (SAWA) based on Semantic Web technologies that facilitates the development of user-defined domain knowledge in the form of formal ontologies and rule sets and then permits the application of the domain knowledge to the monitoring of relevant relations as they occur in a situations. SAWA includes tools for developing ontologies in OWL and rules in SWRL and provides runtime components for collecting event data, storing and querying the data, monitoring relevant relations and viewing the results through a graphical user interface. An application of SAWA to a scenario from the domain of supply logistics is presented along with a discussion of the challenges encountered in using SWRL for this task. [ABSTRACT FROM AUTHOR]

Metadata have been already given to most of the data and objects in the real world, such as books, foods, digital contents like movie, electric devices, and so forth. Further, they can be accumulated electronically by barcodes and RFIDs, which is expected to spread explosively in 2005. On the other hand, web services are getting popular in the internet, and UPnP services and ECHONET are penetrating into the home network. In our project, we propose a new handheld application called Ubiquitous Service Finder, in which user can intuitively browse as icons the metadata around him/her in a cellular phone, then invoke the services semantically related to the metadata by simple drag and drop operation. [ABSTRACT FROM AUTHOR]

Web services can be presented to end-users via user interfaces (UIs) that facilitate the invocation of these services. Standardized, interoperable mechanisms for describing Web service interfaces enable the generation of UIs automatically and dynamically, at least in principle; the emergence of Semantic Web services opens the possibility of improving the generation process. In this paper, we propose a scheme that extends the OWL-S ontology, an emerging standard for Semantic Web services, to better enable the creation of such dynamic interfaces. Semantic Web services go beyond "classical" Web services in enabling enhanced discovery, invocation and composition. In our scheme, the integration of semantic descriptions of Web services with semantic models of the user's locally available data enables context-based personalization of dynamically created user interfaces, allowing us to minimize the number of necessary inputs. The need for this is compelling on mobile devices with limitations on input methods and screen size and where context data is readily available. The use of an underlying semantic model enables better accuracy than traditional form-filling techniques. We propose an architecture for the creation and personalization of dynamic UIs from Web service descriptions. The key idea is to exploit the semantic relationships between type information of Web service input fields, and their association with information the system has about the user (such as the user's current context, PIM data, context history, usage history, corporate data etc.), in order to personalize and simplify the invocation of Web services. [ABSTRACT FROM AUTHOR]

Semantic Web, using formal languages to represent document content and providing facilities for aggregating information spread around, can improve the functionalities provided nowadays by KM tools. This paper describes a Knowledge Management system, targeted at lawyers, which has been enhanced using Semantic Web technologies. The system assists lawyers during their everyday work, and allows them to manage their information and knowledge. A semantic layer has been added to the system, providing capabilities that make system usage easier and much more powerful, adding new and advanced means for create, share and access knowledge. [ABSTRACT FROM AUTHOR]

Structured Clinical Documentation is a fundamental component of the healthcare enterprise, linking both clinical (e.g., electronic health record, clinical decision support) and administrative functions (e.g., evaluation and management coding, billing). Documentation templates have proven to be an effective mechanism for implementing structured clinical documentation. The ability to create and manage definitions, i.e., definitions management, for various concepts such as diseases, drugs, contraindications, complications, etc. is crucial for creating and maintaining documentation templates in a consistent and cohesive manner across the organization. Definitions management involves the creation and management of concepts that may be a part of controlled vocabularies, domain models and ontologies. In this paper, we present a real-world implementation of a semantics-based approach to automate structured clinical documentation based on a description logics (DL) system for ontology management. In this context we will introduce the ontological underpinnings on which clinical documents are based, namely the domain, document and presentation ontologies. We will present techniques that leverage these ontologies to render static and dynamic templates that contain branching logic. We will also evaluate the role of these ontologies in the context of managing the impact of definition changes on the creation and rendering of these documentation templates, and the ability to retrieve documentation templates and their instances precisely in a given clinical context. [ABSTRACT FROM AUTHOR]

Killer apps are highly transformative technologies that create new markets and widespread patterns of behaviour. IT generally, and the Web in particular, has benefited from killer apps to create new networks of users and increase its value. The Semantic Web community on the other hand is still awaiting a killer app that proves the superiority of its technologies. There are certain features that distinguish killer apps from other ordinary applications. This paper examines those features in the context of the Semantic Web, in the hope that a better understanding of the characteristics of killer apps might encourage their consideration when developing Semantic Web applications. [ABSTRACT FROM AUTHOR]

This paper is aimed at documenting the role of Web services and specifically Semantic Web Services in serving the needs of the entertainment industry by enabling the users to easily research and explore the large volume meta-content (content about content e.g. entertainment news, articles, reviews, interviews, trailers etc) and eventually leading them to FIND right content (Music, Movies TV program etc). In this scenario, semantic web techniques are used to not only develop and populate the ontology from different meta-content sources, but also to annotate them semantically to provide personalize meta content based Search-Find experience for main content. The paper outlines an application scenario where this is applied in a demonstrated proof of concept and articulates the next steps in the evolution of this architecture. [ABSTRACT FROM AUTHOR]

Water resource management is becoming increasingly difficult due to the interaction of conflicting factors such as environmental sustainability and economic constraints. In Australia, the introduction of a water rights management framework is an administrative attempt to facilitate the resolution of this complex and multi-faceted problem. Policies relating to water allocation and trading have already advanced beyond our abilities to monitor, measure, report and enforce these policies. Mismanagement of this valued resource can have severe damaging long term environmental and economic effects. We believe that Semantic Web Services technologies will help decision makers minimise the risk of mismanagement. In this paper, we discuss the potential application of our dynamic service composition approach and its compatibility with other solutions. We identify the benefits for the different categories of users and discuss how ontologies can help to bridge the gap between specialists and non-specialists, or specialists focusing on separate aspects of the overall problem. [ABSTRACT FROM AUTHOR]

This paper describes the design of and the deployment options for the Federal Enterprise Architecture Reference Model Ontology (FEA-RMO). The goal of any reference model is to provide a basis or starting point for some design process. While this is a laudable goal, it poses an immediate problem for representation; how can a model be represented in such a way that it can be extended in certain ways (for application to a particular problem), but not without regard to the advice that it gives? Reference models are usually expressed in natural language. At their best, such models provide a starting point for designers, and a checklist for their designs, to see that they conform to industry best practices. At worst, reference models expressed in natural language become a source of busy work; designers do not use the models during the design process, instead they spend time after the fact writing up an explanation of how and why they are compliant with the reference framework they've never seriously considered. In this paper, we have used Semantic Web technologies (in particular, RDF and OWL) to represent a reference mode for enterprise architecture in the US government. The content of the model comes from the recent Federal Enterprise Architecture Reference Model effort. We use the capability of RDF to distribute structured information to allow the reference model to be extended (as intended in its design). We use OWL to maintain the consistency of those extensions. The model has been used as the basis for an implementation of an FEA registry, a web-based system for managing enterprise architectures based on the FEA. The work of representing the FEA as formal ontologies was funded in part by GSA. We would like to thank Rick Murphy, Enterprise Architect and George Thomas, Chief Enterprise Architect of the Office of CIO of GSA for their vision, support and contribution to the use cases described in this paper. Keywords: Government Sector, Portals, Knowledge Management. [ABSTRACT FROM AUTHOR]

E-Science experiments typically involve many distributed services maintained by different organisations. After an experiment has been executed, it is useful for a scientist to verify that the execution was performed correctly or is compatible with some existing experimental criteria or standards. Scientists may also want to review and verify experiments performed by their colleagues. There are no exsiting frameworks for validating such experiments in today's e-Science systems. Users therefore have to rely on error checking performed by the services, or adopt other ad hoc methods. This paper introduces a platform-independent framework for validating workflow executions. The validation relies on reasoning over the documented provenance of experiment results and semantic descriptions of services advertised in a registry. This validation process ensures experiments are performed correctly, and thus results generated are meaningful. The framework is tested in a bioinformatics application that performs protein compressibility analysis. [ABSTRACT FROM AUTHOR]

We present a method for rapid development of benchmarks for Semantic Web knowledge base systems. At the core, we have a synthetic data generation approach for OWL that is scalable and models the real world data. The data-generation algorithm learns from real domain documents and generates benchmark data based on the extracted properties relevant for benchmarking. We believe that this is important because relative performance of systems will vary depending on the structure of the ontology and data used. However, due to the novelty of the Semantic Web, we rarely have sufficient data for benchmarking. Our approach helps overcome the problem of having insufficient real world data for benchmarking and allows us to develop benchmarks for a variety of domains and applications in a very time efficient manner. Based on our method, we have created a new Lehigh BibTeX Benchmark and conducted an experiment on four Semantic Web knowledge base systems. We have verified our hypothesis about the need for representative data by comparing the experimental result to that of our previous Lehigh University Benchmark. The difference in both experiments has demonstrated the influence of ontology and data on the capability and performance of the systems and thus the need of using a representative benchmark for the intended application of the systems. [ABSTRACT FROM AUTHOR]

Triple20 is a ontology manipulation and visualization tool for languages built on top of the Semantic-Web RDF triple model. In this article we explain how a triple-centered design compares to the use of a separate proprietary internal data model. We show how to deal with the problems of such a low-level data model and show that it offers advantages when dealing with inconsistent or incomplete data as well as for integrating tools. [ABSTRACT FROM AUTHOR]

We show how state-of-the-art Semantic Web technology can be used in e-Science, in particular, to automate the classification of proteins in biology. We show that the resulting classification was of comparable quality to that performed by a human expert, and how investigations using the classified data even resulted in the discovery of significant information that had previously been overlooked, leading to the identification of a possible drug-target. [ABSTRACT FROM AUTHOR]

After becoming a W3C Recommendation, OWL is becoming increasingly widely accepted and used. However most people still find it difficult to create and use OWL ontologies. On major difficulty is "debugging" the ontologies - discovering why a reasoners has inferred that a class is "unsatisfiable" (inconsistent). Even for people who do understand OWL and the logical meaning of the underlining description logic, discovering why concepts are unsatisfiable can be difficult. Most modern tableaux reasoners do not provide any explanation as to why the classes are unsatisfiable. This paper presents a ‘black boxed' heuristic approach based on identifying common errors and inferences. [ABSTRACT FROM AUTHOR]

OntoClean is a unique approach towards the formal evaluation of ontologies, as it analyses the intensional content of concepts. Although it is well documented in numerous publications, and its importance is widely acknowledged, it is still used rather infrequently due to the high costs for applying OntoClean, especially on tagging concepts with the correct meta-properties. In order to facilitate the use of OntoClean and to enable proper evaluation of it in real-world cases, we provide AEON , a tool which automatically tags concepts with appropriate OntoClean meta-properties. The implementation can be easily expanded to check the concepts for other abstract meta-properties, thus providing for the first time tool support in order to enable intensional ontology evaluation for concepts. Our main idea is using the web as an embodiment of objective world knowledge, where we search for patterns indicating concepts meta-properties. We get an automatic tagging of the ontology, thus reducing costs tremendously. Moreover, AEON lowers the risk of having subjective taggings. As part of the evaluation we report our experiences from creating a middle-sized OntoClean-tagged reference ontology. [ABSTRACT FROM AUTHOR]

In many practical applications, ontologies tend to be very large and complicated. In order for users to quickly understand and analyze large-scale ontologies, in this paper we propose a novel ontology visualization approach, which aims to complement existing approaches like the hierarchy graph. Specifically, our approach produces a holistic "imaging" of the ontology which contains a semantic layout of the ontology classes. In addition, the distributions of the ontology instances and instance relations are also depicted in the "imaging". We introduce at length the key techniques and algorithms used in our approach. Then we examine the resulting user interface and find it facilitates tasks like ontology navigation, ontology retrieval and ontology instance analysis. [ABSTRACT FROM AUTHOR]

We discuss four linguistic ontology-mapping techniques and evaluate them on real-life ontologies in the domain of food. Furthermore we propose a method to combine ontology-mapping techniques with high Precision and Recall to reduce the necessary amount of manual labor and computation. [ABSTRACT FROM AUTHOR]

In this paper we benchmark three popular database representations of RDF/S schemata and data: (a) a schema-aware (i.e., one table per RDF/S class or property) with explicit (ISA) or implicit (NOISA) storage of subsumption relationships, (b) a schema-oblivious (i.e., a single table with triples of the form $\langle$subject-predicate-object$\rangle$), using (ID) or not (URI) identifiers to represent resources and (c) a hybrid of the schema-aware and schema-oblivious representations (i.e., one table per RDF/S meta-class by distinguishing also the range type of properties). Furthermore, we benchmark two common approaches for evaluating taxonomic queries either on-the-fly (ISA, NOISA, Hybrid), or by precomputing the transitive closure of subsumption relationships (MatView, URI, ID). The main conclusion drawn from our experiments is that the evaluation of taxonomic queries is most efficient over RDF/S stores utilizing the Hybrid and MatView representations. Of the rest, schema-aware representations (ISA, NOISA) exhibit overall better performance than URI, which is superior to that of ID, which exhibits the overall worst performance. [ABSTRACT FROM AUTHOR]

This paper presents serse - SEmantic Routing SystEm- a distributed multi-agent system composed of specialised agents that provides robust and efficient gathering and aggregation of digital content from diverse resources. The agents composing serse use ontological descriptions to search and retrieve semantically annotated knowledge sources, by maintaining a semantic index of the instances of the annotation ontology. The efficient retrieval is made it possible through the semantic routing mechanism, that permits to identify the agent indexing the resources requested by a user query without having to maintain a central index, and by reducing the number of messages broadcasted to the system. The system is also capable of exhibiting autonomic behaviour. Autonomic behaviour is characterised by self configuration and self healing capabilities, aimed at permitting the system to manage the failure of one of its agents and ensure continuous functioning. [ABSTRACT FROM AUTHOR]

Coordination is the process of managing the possible interactions between activities and processes; a mechanism to handle such interactions is known as a coordination regime. A successful coordination regime will prevent negative interactions occurring (e.g., by preventing two processes from simultaneously accessing a non-shareable resource), and wherever possible will facilitate positive interactions (e.g., by ensuring that activities are not needlessly duplicated). We start from the premise that effective coordination mechanisms require the sharing of knowledge about activities, resources and their properties, and hence, that in a heterogeneous environment, an ontological approach to coordination is appropriate. After surveying recent work on dynamic coordination, we describe an ontology for coordination that we have developed with the goal of coordinating semantic web processes. We then present a implementation of our ideas, which serves as a proof of concept for how this ontology can be used for dynamic coordination. We conclude with a summary of the presented work, illustrate its relation to the Semantic Web, and provide insights into future extensions. [ABSTRACT FROM AUTHOR]

This paper extends the model theory of RDF with rules, placing an emphasis on integration with OWL and decidability of entailment. We start from an abstract syntax that views a rule as a pair of rule graphs which generalize RDF graphs by also allowing rule variables in subject, predicate and object positions. We include RDFS as well as a decidable part of OWL that weakens D-entailment and OWL Full. Classes can be used as instances. Almost all examples in the DAML set of test rules are covered by our approach. For a set of rules R, we define a general notion of R-entailment. Extending earlier results on RDFS and OWL, we prove a general completeness result for R-entailment. This result shows that a restricted form of application of rules that introduce blank nodes is sufficient to determine R-entailment. For rules that do not introduce blank nodes, we prove that R-entailment and R-consistency are decidable and in PSPACE. For rules that do not introduce blank nodes and that satisfy a bound on the size of rule bodies, we prove that R-consistency is in P, that R-entailment is in NP, and that R-entailment is in P if the target RDF graph is ground. [ABSTRACT FROM AUTHOR]

Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with contradicting or overlapping parts. For this reason ontologies need to be brought into mutual agreement (aligned). One important method for ontology alignment is the comparison of class and property names of ontologies using string-distance metrics. Today quite a lot of such metrics exist in literature. But all of them have been initially developed for different applications and fields, resulting in poor performance when applied in this new domain. In the current paper we present a new string metric for the comparison of names which performs better on the process of ontology alignment as well as to many other field matching problems. [ABSTRACT FROM AUTHOR]

Semantic query optimization (SQO) has been proved to be quite useful in various applications (e.g., data integration, graphical query generators, caching, etc.) and has been extensively studied for relational, deductive, object, and XML databases. However, less attention to SQO has been devoted in the context of the Semantic Web. In this paper, we present sound and complete algorithms for the containment and minimization of RDF/S query patterns. More precisely, we consider two widely used RDF/S query fragments supporting pattern matching at the data, but also, at the schema level. To this end, we advocate a logic framework for capturing the RDF/S data model and semantics and we employ well-established techniques proposed in the relational context, in particular, the Chase and Backchase algorithms. [ABSTRACT FROM AUTHOR]

Domain ontologies very rarely model verbs as relations holding between concepts. However, the role of the verb as a central connecting element between concepts is undeniable. Verbs specify the interaction between the participants of some action or event by expressing relations between them. In parallel, it can be argued from an ontology engineering point of view that verbs express a relation between two classes that specify domain and range. The work described here is concerned with relation extraction for ontology extension along these lines. We describe a system (RelExt) that is capable of automatically identifying highly relevant triples (pairs of concepts connected by a relation) over concepts from an existing ontology. RelExt works by extracting relevant verbs and their grammatical arguments (i.e. terms) from a domain-specific text collection and computing corresponding relations through a combination of linguistic and statistical processing. The paper includes a detailed description of the system architecture and evaluation results on a constructed benchmark. RelExt has been developed in the context of the SmartWeb project, which aims at providing intelligent information services via mobile broadband devices on the FIFA World Cup that will be hosted in Germany in 2006. Such services include location based navigational information as well as question answering in the football domain. [ABSTRACT FROM AUTHOR]

Visiting museums is an increasingly popular pastime. Studies have shown that visitors can draw on their museum experience, long after their visit, to learn new things in practical situations. Rather than viewing a visit as a single learning event, we are interested in ways of extending the experience to allow visitors to access online resources tailored to their interests. Museums typically have extensive archives that can be made available online, the challenge is to match these resources to the visitor's interests and present them in a manner that facilitates exploration and engages the visitor. We propose the use of knowledge level resource descriptions to identify relevant resources and create structured presentations. A system that embodies this approach, which is in use in a UK museum, is presented and the applicability of the approach to the broader semantic web is discussed. [ABSTRACT FROM AUTHOR]

In this article, we propose a new ontology evolution approach that combines a top-down and a bottom-up approach. This means that the manual request for changes (top-down) by the ontology engineer is complemented with an automatic change detection mechanism (bottom-up). The approach is based on keeping track of the different versions of ontology concepts throughout their lifetime (called virtual versions). In this way, changes can be defined in terms of these virtual versions. [ABSTRACT FROM AUTHOR]

This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs. Probabilities needed for constructing conditional probability tables (CPT) during translation and for measuring semantic similarity during mapping are learned using text classification techniques where each concept in an ontology is associated with a set of semantically relevant text documents, which are obtained by ontology guided web mining. The basic ideas of this approach are validated by positive results from computer experiments on two small real-world ontologies. [ABSTRACT FROM AUTHOR]

A common practice in conceptual modeling is to separate the intensional from the extensional model. Although very intuitive, this approach is inadequate for many complex domains, where the borderline between the two models is not clear-cut. Therefore, OWL-Full, the most expressive of the Semantic Web ontology languages, allows combining the intensional and the extensional model by a feature we refer to as metamodeling. In this paper, we show that the semantics of metamodeling adopted in OWL-Full leads to undecidability of basic inference problems, due to free mixing of logical and metalogical symbols. Based on this result, we propose two alternative semantics for metamodeling: the contextual and the HiLog semantics. We show that $\mathcal{SHOIQ}$ — a description logic underlying OWL-DL — extended with metamodeling under either semantics is decidable. Finally, we show how the latter semantics can be used in practice to axiomatize the logical interaction between concepts and metaconcepts. [ABSTRACT FROM AUTHOR]

Most existing ontology mapping tools are inexact. Inexact ontology mapping rules, if not rectified, result in imprecision in the applications that use them. We describe a framework to probabilistically improve existing ontology mappings using a Bayesian Network. Omen, an Ontology Mapping ENhancer, is based on a set of meta-rules that captures the influence of the ontology structure and the existing matches to match nodes that are neighbours to matched nodes in the two ontologies. We have implemented a protype ontology matcher that can either map concepts across two input ontologies or enhance existing matches between ontology concepts. Preliminary experiments demonstrate that Omen enhances existing ontology mappings in our test cases. [ABSTRACT FROM AUTHOR]

In our work we extend the traditional bipartite model of ontologies with the social dimension, leading to a tripartite model of actors, concepts and instances. We demonstrate the application of this representation by showing how community-based semantics emerges from this model through a process of graph transformation. We illustrate ontology emergence by two case studies, an analysis of a large scale folksonomy system and a novel method for the extraction of community-based ontologies from Web pages. [ABSTRACT FROM AUTHOR]

Often the challenge of finding relevant information is reduced to find the ‘right' people who will answer our question. In this paper we present innovative algorithms called INGA (Interest-based Node Grouping Algorithms) which integrate personal routing indices into semantic query processing to boost performance. Similar to social networks peers in INGA cooperate to efficiently route queries for documents along adaptive shortcut-based overlays using only local, but semantically well chosen information. We propose active and passive shortcut creation strategies for index building and a novel algorithm to select the most promising content providers depending on each peer index with respect to the individual query. We quantify the benefit of our indexing strategy by extensive performance experiments in the SWAP simulation infrastructure. While obtaining high recall values compared to other state-of-the-art algorithms, we show that INGA improves recall and reduces the number of messages significantly. [ABSTRACT FROM AUTHOR]

We propose a declarative update language for RDF graphs which is based on the paradigms of query and view languages RQL and RVL. Our language, called RUL, ensures that the execution of the update primitives on nodes and arcs neither violates the semantics of the RDF model nor the semantics of the given RDFS schema. In addition, RUL supports fine-grained updates at the class and property instance level, set-oriented updates with a deterministic semantics and takes benefit of the full expressive power of RQL for restricting the range of variables to nodes and arcs of RDF graphs. [ABSTRACT FROM AUTHOR]

One of the main goals of the semantic web services effort is to enable automated composition of web services. An end-to-end view of the service composition process involves automation of composite service creation, development of executable workflows and deployment on an execution environment. However, the main focus in literature has been on the initial part of formally representing web service capabilities and reasoning about their composition using AI techniques. Based upon our experience in building an end-to-end composition tool for application integration, we bring out issues that have an impact on information modeling aspects of the composition process. In this paper, we present approaches for solving problems relating to scalability and manageability of service descriptions and data flow construction for operationalizing the composed services. [ABSTRACT FROM AUTHOR]

Matching hierarchical structures, like taxonomies or web directories, is the premise for enabling interoperability among heterogenous data organizations. While the number of new matching solutions is increasing the evaluation issue is still open. This work addresses the problem of comparison for pairwise matching solutions. A methodology is proposed to overcome the issue of scalability. A large scale dataset is developed based on real world case study namely, the web directories of Google, Looksmart and Yahoo!. Finally, an empirical evaluation is performed which compares the most representative solutions for taxonomy matching. We argue that the proposed dataset can play a key role in supporting the empirical analysis for the research effort in the area of taxonomy matching. [ABSTRACT FROM AUTHOR]