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General purpose ontologies and domain ontologies make up the infrastructure of the Semantic Web, which allow for accurate data representations with relations, and data inferences. In our approach to multimodal dialogue systems providing question answering functionality (SMARTWEB), the ontological infrastructure is essential. We aim at an integrated approach in which all knowledge-aware system modules are based on interoperating ontologies in a common data model. The discourse ontology is meant to provide the necessary dialogue- and HCI concepts. We present the ontological syntactic structure of multimodal question answering results as part of this discourse ontology which extends the W3C EMMA annotation framework and uses MPEG-7 annotations. In addition, we describe an extension to ontological result structures where automatic and context-based sorting mechanisms can be naturally incorporated.

Publications Managing Ontology Lifecycles in Corporate Settings Markus Luczak-Rösch and Ralf Heese: Managing Ontology Lifecycles in Corporate Settings, International Conference on Semantic Systems (I-SEMANTICS), Graz, Austria, September 03-05, 2008 Interoperability Issues, Ontology Matching and MOMA Malgorzata Mochol: Interoperability Issues, Ontology Matching and MOMA, International Conference on Semantic Systems (I-SEMANTICS), Graz, Austria, September 03-05, 2008 Towards a rule-based matcher selection Malgorzata Mochol, Anja Jentzsch: Towards a rule-based matcher selection, 6th International Conference on Knowledge Engineering and Knowledge Management Knowledge Patterns (EKAW2008), Acitrezza, Catania, Italy, September 29 - October 03, 2008 Simple Back-end Services for Corporate Semantic Web Robert Tolksdorf, Radoslaw Oldakowski, Thomas Hoppe: Simple Back-end Services for Corporate Semantic Web, 3rd International Workshop on Applications of Semantic Technologies (AST 2008) at INFORMATIK 2008, Munich, Germany, September 2008. (Abstract) A Generic Corporate Ontology Lifecycle Markus Luczak-Rösch and Ralf Heese: A Generic Corporate Ontology Lifecycle, 3rd Workshop on Semantic Wikis, European Semantic Web Conference, June 2008 (Abstract, Poster)

Synonyms computational ontology, semantic data model, ontological engineering Definition In the context of computer and information sciences, an ontology defines a set of representational primitives with which to model a domain of knowledge or discourse. The representational primitives are typically classes (or sets), attributes (or properties), and relationships (or relations among class members). The definitions of the representational primitives include information about their meaning and constraints on their logically consistent application.

"2009-09-01 [09:30 - 11:00] : Session 3A: Web, Semantics and Ontologies I" 2009-09-01 [14:00 - 15:30] : Session 4A: Web, Semantics and Ontologies II 2009-09-01 [16:00 - 17:30] : Session 5A: Web, Semantics and Ontologies III 2009-09-02 [09:30 - 11:00] : Session 6B: Semantic Web and Ontologies IV (short papers)

This paper presents an ontology-based framework aimed at explicitly representing the context of the use of a learning object inside of a learning design. The core of the proposed framework is a learning object context ontology that leverages a range of other kinds of learning ontologies (e.g. domain, user modeling, learning design etc.) to capture the context-specific metadata. On top of that framework, we develop the architecture of an adaptive educational system, in order to illustrate the benefits of our proposal for personalization of learning design. Finally, we reflect on how two present educational tools (iHelp Courses and TANGRAM) correspond to the proposed architecture.

"A naïve ontology for concepts of time and space for searching and learning" Introduction. In this paper, we propose a new approach for developing naïve ontology as the basis for optimal information access interfaces for multimedia digital documents intended for novice users. Method. We try to elicit the knowledge structure of domain novices and patterns of its modification in their searching and learning processes by eye-tracker and showing eye-movements in the post-search interviews. Analysis. Recorded interview data were fully transcribed and coded using Atlas.ti and analysed following a bottom-up strategy of the constant-comparative technique. Results. We developed a taxonomy of knowledge modification which includes (1) adding, (2) correcting, (3) limiting, (4) relating, (5) specifying and (6) transforming. Conclusion.The taxonomy may be expanded and elaborated as the project progress and findings are expected to be incorporated into the design of the naïve ontology. The study results provided theoretical implications on knowledge building, methodological implications on data collection using eye-tracker and showing eye-movements in the post-search interviews and useful information on the design of information access interface for novices users.

What is LOCO-Analyst? LOCO-Analyst is an educational tool aimed at providing teachers with feedback on the relevant aspects of the learning process taking place in a web-based learning environment, and thus helps them improve the content and the structure of their web-based courses. LOCO-Analyst aims at providing teachers with feedback regarding: *  all kinds of activities their students performed and/or took part in during the learning process, *  the usage and the comprehensibility of the learning content they had prepared and deployed in the LCMS, *  contextualized social interactions among students (i.e., social networking) in the virtual learning environment. This Web site provides some basic information about LOCO-Analyst, its functionalities and implementation. In addition, you can watch videos illustrating the tool's functionalities. You can also learn about the LOCO (Learning Object Context Ontologies) ontological framework that lies beneath the LOCO-Analyst tool and download the ontologies of this framework.

Tom Gruber at Stanford University defines and conceptualizes ontologies as they are applied to the semantic web.

The paper describes some models for knowledge construction and analyzes them in terms of their suitability as instruments for the introduction of semantics on the web. The paper then provides evidence regarding some limits for the systematic use of semantic search engine and ontology domain systems in everyday teaching and knowledge construction.

IBM To represent the Semantic Web, you'll use the following technologies: * A global naming scheme (URIs) * A standard syntax for describing data (RDF) * A standard means of describing the properties of that data (RDF Schema) * A standard means of describing relationships between data items (ontologies defined with the OWL Web Ontology Language) Let's take a closer look at these technologies.

Topic: Semantic Web Recent Posts in this Topic 5Cs Dave Snowden revises and reprises his conditions of complexity. Including this one: "Constraint is key to understanding complexity, it governs the transition between the three ontologies. Increase constraint and you create an ordered system; do that inappropriately and you create the conditions for catastrophic failure; remove constraint and the system is chaotic. Lightly constrain the system, while allowing it to be modified by the actors within it and you enable evolution and the emergence of meaning. Managing constrains is one of the things you can train managers to do, and measure their capability and effectiveness." Do I agree with that? I don't know. How do you constrain them. Who does the constraining? With networks there can be natural limits, which prevents them from being scale free. But I don't think this is what Snowden means. Dave Snowden, Cognitive Edge, October 23, 2008 [Link] [Tags: Ontologies, Networks, Semantic Web] [Comment]

"Many languages are in serious danger of being lost and if nothing is done to prevent it, half of the world's approximately 6,500 languages will disappear in the next 100 years. Language data are central to the research of a large social science community, including linguists, anthropologists, archeologists, historians, sociologists, and political scientists interested in the culture of indigenous people. The death of a language entails the loss of a community's traditional culture, for the language is a unique vehicle for its traditions and culture. In this paper, we describe the effort undertaken at Wayne State University to preserve endangered languages using the state-of-the-art information technologies. We discuss the issues involved in such an effort, and present the architecture of a distributed digital library which will contain various data of endangered languages in the forms of text, image, video and audio files and include advanced tools for intelligent cataloguing, indexing, searching and browsing information on languages and language analysis. Various Semantic Web technologies such as XML, OLAC, and ontologies are used so that the digital library is developed as a useful linguistic resource on the Semantic Web."

Semantic Web applications offer great potential to student modellers who have traditionally struggled with issues of re-use, portability and tight coupling with learning applications. In this paper, we describe our use of ontology languages and elearning standards to develop a loosely coupled and portable student modelling architecture used in a large-scale, distributed production learning environment.

OWL Resource: definitions, specifications, etc.

The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it? Two main challenges can be seen in this direction: on the one hand, to achieve interoperability among various educational systems and on the other hand, to have automated, structured and unified authoring support for their creation. In the spirit of the Semantic Web a key to enabling the interoperability is to capitalize on the (1) semantic conceptualization and ontologies, (2) common standardized communication syntax, and (3) large-scale service-based integration of educational content and functionality provision and usage.

Franz Inc. is the leading supplier of commercial, persistent and scalable RDF Graph Database products. AllegroGraph RDFStore provides the solid storage layer for powerful reasoning and ontology modeling capabilities. Franz's semantic technology solutions are uniquely positioned to help bring your Web 3.0 ideas to reality.

A complex set of extensions to the World Wide Web, the Semantic Web will make data and services more accessible to computers and useful to people. Some of these extensions are being deployed, and many are coming in the next years. This is the only book to explore the territory of the Semantic Web in a broad and conceptual manner. This Guide acquaints you with the basic ideas and technologies of the Semantic Web, their roles and inter-relationships. The key areas covered include knowledge modeling (RDF, Topic Maps), ontology (OWL), agents (intelligent and otherwise), distributed trust and belief, "semantically-focused" search, and much more. The book's basic, conceptual approach is accessible to readers with a wide range of backgrounds and interests. Important points are illustrated with diagrams and occasional markup fragments. As it explores the landscape it encounters an ever-surprising variety of novel ideas and unexpected links. The book is easy and fun to read - you may find it hard to put down.

eLearning is fast, relevant and just-in-time learning grown from the learningrequirements of the new, dynamically changing, distributed business world. The term „Semantic Web" encompasses efforts to build a new WWW architecture that supports content with formal semantics, which enables better possibilities for searching and navigating through the cyberspace. As such, the Semantic Web represents a promising technology for realizing eLearning requirements. This paper presents an approach for implementing the eLearning scenario using Semantic Web technologies. It is primarily based on ontology-based descriptions of content, context and structure of the learning materials and benefits the providing of and accessing to the learning materials.

About the Conference The vision of the Semantic Web is to enhance today's Web by exploiting machine-processable metadata. The explicit representation of the semantics of data, enriched with domain theories (ontologies), will enable a web that provides a qualitatively new level of service. It will weave together a large network of human knowledge and makes this knowledge machine-processable. Various automated services will help the users to achieve their goals by accessing and processing information in machine-understandable form. This network of knowledge systems will ultimately lead to truly intelligent systems, which will be employed for various complex decision-making tasks.

ur patented Metatomix Platform for Life Sciences harnesses the power of semantic web standards and combines ontology-based modeling, middleware integration, business rules processing and advanced data visualization that delivers seamless unification and enrichment of disparate data sources (both structured and unstructured), makes the enriched information actionable and provides insights into the information that were previously unavailable.