SemanticWeb Research

How Semantic Web Technologies are Enabling the Bench to Bedside Vision Summary *Semantic Web Technologies help to integrate diverse data sets *Beneficial for drug safety and personalized medicine *Triple stores and on-the-fly mappings *Many organizations are deploying Semantic Web solutions in the life sciences

TopQuadrant assists customers in planning, designing and deploying semantic solutions that enable systems and people to quickly fuse relevant information from diverse sources, put knowledge into context, collaborate effectively, and make better decisions. We provide structured solution packages that combine: * Open architecture platform built specifically to implement W3C semantic web standards * Integration with the best of breed third party components * Training and mentoring on the applications of Semantic Web technology * Proven methodology fine tuned to the implementation needs of the semantic solutions * Planning, modeling and implementation services

The scope of the UMLS Semantic Network is broad, allowing for the semantic categorization of a wide range of terminology in multiple domains. Major groupings of semantic types include organisms, anatomical structures, biologic function, chemicals, events, physical objects, and concepts or ideas. The links between the semantic types provide the structure for the network and represent important relationships in the biomedical domain. The primary link between the semantic types is the 'isa' link. The 'isa' link establishes the hierarchy of types within the Network and is used for deciding on the most specific semantic type available for assignment to a Metathesaurus concept. There is also a set of non-hierarchical relationships, which are grouped into five major categories: `physically related to,' `spatially related to,' `temporally related to,' `functionally related to,' and `conceptually related to.'

A semantic network is a directed graph consisting of nodes (also termed points or vertices) which represent concepts and edges (also termed lines or arcs) which represent semantic relations between the concepts. A kind of knowledge representation used, for example, in hypertext systems.

Abstract. Recent developments in Web technologies and using AI techniques to support efforts in making the Web more intelligent and provide higher-level services to its users have opened the door to building the Semantic Web. That fact has a number of important implications for Web-based education, since Web-based education has become a very important branch of educational technology. Classroom independence and platform independence of Web-based education, availability of authoring tools for developing Web-based courseware, cheap and efficient storage and distribution of course materials, hyperlinks to suggested readings, digital libraries, and other sources of references relevant for the course are but a few of a number of clear advantages of Web-based education.

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.

We present an approach to hybrid semantic Web service matching that complements logic based reasoning with approximate matching based on syntactic IR based similarity computations. The hybrid matchmaker, called OWLS-MX, applies this approach to services and requests specified in OWL-S. Experimental results of measuring performance and scalability of different variants of OWLS-MX show that under certain constraints logic based only approaches to OWLS service I/O matching can be significantly outperformed by hybrid ones.

Topics in education are changing with an ever faster pace. ELearning resources tend to be more and more decentralized. Users increasingly need to be able to use the resources of the web. For this, they should have tools for finding and organizing information in a decentralized way. In this paper, we show how an ontologybased tool suite allows to make the most of the resources available on the web.

Traditionally, visitors to museums have been left having to choose between finding their way around exhibits on their own or taking a standardized group tour with a guide. In this paper, we describe a context-aware museum tour guide that adjusts its recommendations to the interests and contexts of individual visitors and enables them to selectively share their experience with others. The tour guide is built around an innovative semantic Web framework that minimizes the development and maintenance costs associated with the introduction of new exhibits, new visitor-oriented services and new sources of contextual information. In particular, it features a semantic Web rule reasoning engine that enables visitor-oriented services to identify relevant sources of contextual information and to enforce user-specified privacy preferences about what information they are willing to share with others (e.g. "only members of my group can see my current location", or "only my friends can see how I rate exhibits"). While still in prototype stage, the tour guide's target environment is the National Museum of Natural Science, one of Taiwan's largest museums with over 3 million visitors per year.

At the ACM Hypertext Conference a panel discussed "The Next Big Thing Inc." in the area of hypertext and hypermedia. The Web has been the "Big Thing" during the past 10 years, but its success has also made it very difficult to find the appropriate information in an ocean of over 3 billion pages. Whereas search engines achieve incredible precision, they suffer from the same "one size fits all" approach that characterizes the Web sites they index. The paper defends the position that personalization, and in particular automatic personalization or adaptation, is the key to reach the goal of offering each individual user (or user group) the information they need. During the panel discussion there was debate about whether the user should always have access and control over the entire (hypertextual) information space. There were different views on whether the "right" to all the information is best guaranteed by offering tools that reduce the information space the user perceives so that the user can actually find and reach the information, or by offering unfiltered access to an ocean of information in which everything is available but in which perhaps nothing can be found. We argue in favor of adaptation but at the same time point out flaws in the way adaptive hypermedia has been used until now. The paper then proposes a new, modular adaptive hypermedia architecture that should lead to adaptive Web-based systems as the "Next Big Thing" indeed.

The application of "Semantic Web" technologies to learning processes is receiving an increasing attention from the perspective of facilitating the selection, delivery and tailoring of learning experiences. But most of the current approaches are centered on the final interaction of the learner with the "learning objects" provided for him/her, neglecting the organizational perspective. From the viewpoint of an organization, the application of Semantic Web technologies should be motivated by the improvement of learning-oriented mechanisms, including both cultural and structural aspects, and considering the ideal of achieving a state of continuous improvement in learning behavior. Such an approach to achieving a "semantic learning organization" gives a complementary perspective to existing "educational Semantic Web" propositions. In this paper, the potential role of the Semantic Web as a driver for enhanced learning organizations is analyzed, and a conceptual framework for the notion of a semantic learning organization is provided.

To say that the Web has affected many societies and cultures is to understate its impact along several dimensions. The Web is a technology which not only affects, but in some sense encompasses societies, cultures, and certainly institutions. Higher education -- at least in the cluster of ways in which it is practiced in the US, the EU, and Japan -- is one such bundle of social institutions affected and encompassed by the Web. While it is possible to overstate or mis-state the Web's effect, whether on higher education or on other institutional clusters, the encompassing reach of the technology, used in every country on Earth by literally tens of millions of users, makes it clear that the Web truly has a revolutionary effect. However, exploring what the Web has affected and continues to effect is a necessary element of any accurate estimation of how the newly emerging Semantic Web may, in its turn, effect societies, cultures, and institutional clusters like higher education.

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.

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.

Welcome to the laboratory for Advanced Research in Intelligent Educational Systems (ARIES). The lab was founded in 1987 with the goal of deepening both research and practice in intelligent systems and how they apply to teaching and learning. Faculty, staff, and students within the laboratory contribute to numerous academic areas, such as user modeling, artificial intelligence, adaptive hypermedia, e-learning, and information visualization.

ARIES is working on the application details alluded to in my semantic web paper.

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.

Recent developments in Web technologies and using AI techniques to support efforts in making the Web more intelligent and provide higher-level services to its users have opened the door to building the Semantic Web. That fact has a number of important implications for Web-based education, since Web-based education has become a very important branch of educational technology. Classroom independence and platform independence of Web-based education, availability of authoring tools for developing Web-based courseware, cheap and efficient storage and distribution of course materials, hyperlinks to suggested readings, digital libraries, and other sources of references relevant for the course are but a few of a number of clear advantages of Web-based education. However, there are several challenges in improving Web-based education, such as providing for more adaptivity and intelligence. Developments in the Semantic Web, while contributing to the solution to these problems, also raise new issues that must be considered if we are to progress. This paper surveys the basics of the Semantic Web and discusses its importance in future Web-based educational applications.

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.

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.