Catálogo de publicaciones - libros

Topic mapping plays several important roles in augmentation of human cognitive capabilities and relational thinking. We summarize three such roles as resource indexing, culture fusion, and modeling. Based on a working hypothesis that combinations of technologies can benefit topic mapping capabilities, we sketch a proposed marriage between Conceptual Graphs and the TMRM variant, Subject Maps. The marriage of technologies is shown to be one of several ways forward for topic mapping.

Nowadays, data handled by an institution or company is spread out by more than one database and lots of documents of different types. To extract the information implicit in that data, it is necessary to pick parts from those various archives. To obtain a general overview, those information slices should be integrated. Different approaches can be followed to achieve that integration, ranging from the merge of resources till the fusion of the extracted parts. In this paper, we introduce Metamorphosis – a Topic Maps oriented environment that enables a conceptual navigation among heterogenous information systems – and we argue that Metamorphosis can be used to achieve, via Topic Maps, the referred semantic integration.

The Office Objects Concept Glossary Manager (CGM), which has been designed by the author as a software component of the ICONS system, helps to create, edit and visualize topic maps. Interesting features of the CGM are distributed topic maps processing, user rights management, topic states and versions management, ontology driven generative user interfaces and Topic Maps Script Language (TMSL). This paper also overviews an example application of the component. In the final section some weaknesses of the CGM are identified and possible improvements are suggested.

One of the most interesting aspects of subject-centric information processing as services is the relationship between resources and subjects. Especially Topic Maps and Published Subjects are core elements of the infrastructure of relationship management. This paper proposes an Application Framework based on Topic Maps. The Application Framework will make possible to realize subject-centric processing. Furthermore in the framework, we can express the semantic distance between topics based on a relationship cost between two nodes of the Topic Map. This paper also introduces some challenges such as software development process and semantic management. Finally, we will overview the on-going on development of the Application Framework to manage those subjects.

This paper describes TMRAP, an abstract web service interface for remote access to topic maps. It can be used to access a topic map repository to query or update a topic map, or to listen for updates to parts of a topic map. An HTTP binding for the interface is presented in this paper; a SOAP binding will be produced in the future.

Published subject indicators (PSI) are public available descriptions of non-addressable subjects. PSI sets can be used as shared vocabulary. Different Topic Map authors can use the same PSI sets to assure that topics dealing with the same subjects are recognized as identical topics by arbitrary Topic Map engines. There is no standardized structure for PSIs or PSI sets. There is no concept for distributed and replicated PSI sets. Both are required features from several application classes. This paper describes how thesauri can be used as a schema for PSI sets and how existing thesauri can be converted to Topic Maps. It is also explained how LDAP can be used as replication platform for PSI sets.

Topic Maps are the international industry standard for semantic information integration. Appropriate means for Topic Map exchange are crucial for its success as integration technology. Topic Map exchange bases on the governing Subject Equality decision approach, the decision whether two Subject Proxies indicate identical Subjects. This paper discusses the ‘absence of shared vocabularies’ in the context of these decisions. Thereby, a differentiation between Referential and Structuralist Subject Equality decision approaches is introduced. All existing approaches to Topic Map exchange base on the TMDM. This implies a Referential Subject Equality decision approach and bound to a concrete Subject Map Disclosure (SMD) ontology and Subject Map (SM) vocabulary. This paper introduces a Structuralist Subject Equality decision approach which is called SIM. It allows the exchange of Topic Maps in the absence of a shared SM ontology and SM vocabulary.

The paper aims to discuss strengths and weaknesses of using Object Role Modeling (ORM) and UML Class Diagrams for conceptual modeling of Topic Maps. Established evaluation criteria for conceptual modeling languages are used to compare Topic Map ontology modeling with ORM and UML, to try to find if ORM is a good alternative to UML. The paper discusses a few extensions to simplify viewing ORM diagrams of a Topic Map ontology. ORM is also used to model a case ontology to show practical use within an application domain.

is an interdisciplinary project running for two years, which is realised in cooperation of several institutions. It aims at developing an information system for a digital collection of different types of visual resources and will combine classical methods of image indexing and retrieval with innovative approaches like content-based image retrieval and the use of topic maps for semantic searching and browsing. This work-in-progress-report outlines the aims of the project and present first results after the period of eleven months.

Topic Maps are means for representing sophisticated, conceptual indexes of any information collection for the purpose of semantic information integration. To properly fulfil this purpose, the generation of Topic Maps has to base on a solid theory. This paper proposes the Observation Principle as the theoretical fundament of a future scientific discipline Topic Maps Engineering. SemanticTalk generates sophisticated, conceptual indexes of speech streams in real-time. Reflecting the Observation Principle, this paper describes how these indexes are created, how they are represented as Topic Maps and how they can be used for semantic information integration purposes.