Information visualisation workshop

Defining and managing semantics and datatypes - Is there a role for ISO 13250 Topic Maps? (Martin Bryan, The SGML Centre)

e-mail: [e-mail]
URL: http://www.diffuse.org

Notion System (R.A. Poell, Netherlands Organisation for Applied Scientific Research (TNO))

Notion System exists since 1991 and can be considered as a prototype of a large-scale implementation. The generated contents consist of concepts (notions) and relationships between them. The multilingual system manages distributed data and is not domain specific. Various levels of detail of information can be registered. There are metadata available for automatic maintenance, filtering et cetera. Exploitation and inference logic are available as notions too. In many aspects Notion System is comparable to RDF(S).

The ideas behind this system can be a possible implementation of the Semantic Web in the future.

The Semantic Web based on these ideas will enable the enhancement of existing techniques (content analyses, NLP, and others) and enable automatic extension of the network. It will also allow new ways of searching and navigating and will promote new presentation techniques (probably 3D or 4D) using context sensitive delivery of information. Agents can deploy automatic information maintenance activities (relevance, validity). Probabilistic answers can be given to some questions, other questions will receive clear answers.

The resulting Semantic Web will be the collaborative work of all users, agents and systems connected to it.

One step further in the future, when the concepts themselves will be agents, the Semantic Web will be enhanced with even more features. Next, when the various devices, up till that moment only connected TO the Web, will be integrated IN the Semantic Web, new openings will be possible.

e-mail: [e-mail]
URL: http://www.tno.nl

The OpenMath project (Mike Dewar, NAG Ltd)

Although mathematical notation is incredibly expressive and flexible, it is also surprisingly ambiguous. OpenMath, developed largely under an IST multimedia project, is a lightweight mechanism for encoding the semantics of mathematical objects so that they can be exchanged between applications and users. When combined with other emerging technologies such as MathML and XSL it has the potential to under-pin a new generation of mathematical applications.

This talk will give a brief technical overview of OpenMath before moving on to discuss how it can be used to build other frameworks and applications such as mathematical components, interactive books, formula databases etc.

See also: http://www.openmath.org

e-mail: [e-mail]
URL: http://www.nag.co.uk

An e-commerce platform for complex configurable products and services (Jürgen Nicklisch-Franken, Persist AG; Heinz Schweppe, FU Berlin)

e-mail: [e-mail]
URL: http://www.persistag.com

Inferential semantics for networked image data: supporting the derivation and management of semantic attributes for Web-based multimedia content (Harold Boley, DFKI, and Jos De Roo, AGFA)

At Agfa, the declarative Eve and Euler systems have been developed for capturing and transforming networked image data. The Euler work has incorporated image annotations on the basis of the W3C's RDF standard. At DFKI, the inference rule system RFML has been developed, which can be applied to annotations for deriving new semantic attributes. The joint RuleML Initiative has started to unify the various markups for XML and RDF inference rules.

In practice, there is a lot of simple rules that can operate on a combination of extracted image features (obtained via image analysis) and additional image-related data. The implicit meaning in image data can thus be made explicit. We study the issue of how to infer (only) meaningful facts from networked image data. In the non-distributed case, the semantics of some centralized image data can be regarded model-theoretically, as the set of facts whose deduction is sanctioned by the given rules. For example, rules can infer the transitive closure of a centralized 'connected' attribute. In the distributed case, we usually have an open network of image data, for which no model-theoretic semantics exists. In the example, the transitive closure of a distributed multi-sensor-derived 'connected' attribute may never form a single stable set.

We thus propose tailored, "least power" mechanisms for inferencing with attributes specific for images such as topology, geometry, texture, and color. These mechanisms will be layered such that the appropriate mechanism is easily identified for each given task (e.g., a functional mechanism will be used for computing with measurements, thus avoiding relational search whenever possible). The work will be done on the basis of real-world (Agfa) image examples and their annotations. The examples will be classified along relevant dimensions, e.g. according to descriptive complexity, for testing the layered inference mechanisms.

Furthermore, to exploit the networked character of the given (Agfa) image data, we will study a "Webized" architecture for distributing inference mechanisms over appropriate subsets of input data, and for channelling output data to possible further processing steps. For this, metadata content and capability descriptions of, respectively, data and mechanisms will be explored. We envisage an efficient, platform-independent Java implementation of the developing inferential semantics for networked image data.

e-mail: [e-mail], [e-mail]
URL: http://www.dfki.uni-kl.de/~boley, http://www.agfa.com

Inducing Semantics from Structures (Paolo Avesani, ITC-IRST)

Our claim is that a new communication protocol could be enabled that is in between a collection of keywords, where terms are not related, and a sentence, where terms are organized in a sequence determined by the rules of natural language. XML documents represent an evidence of how such a kind of communication protocol is spreading.

Consider the scenario where the structured terms represent a web site hierarchy. The term _home_ could refer different meaning: the concept of homepage of the web site, or the personal address of people. We could also represents such a kind of information as a XML document where tags are the terms used to refer the main entry point of a web site, and the structure is derived from the links between URIs. The right meaning of term _home_ will we disambiguated taking into account the related position in the structure: a very narrow position to the root will favor the interpretation of _homepage_, while whether neighbour terms will be related to _address_ or _office_ the interpretation of _domestic location_ will be preferred.

Though the example is really simple, what we would like to stress is that the disambiguation process can detect the right interpretations as result of a learning effort.

e-mail: [e-mail]
URL: http://sra.itc.it
Other contacts: P. Bouquet(University of Trento, http://www.cs.unitn.it ), R. Rizzi(ITC-IRST)