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2006 | Buch

Visualizing the Semantic Web

XML-Based Internet and Information Visualization

herausgegeben von: Vladimir Geroimenko, DSc, PhD, MSc, Chaomei Chen, PhD, MSc, BSc

Verlag: Springer London

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The Semantic Web is a vision that has sparked a wide-ranging enthusiasm for a new generation of the Web. The Semantic Web is happening. The central idea of that vision is to make the Web more understandable to computer programs so that people can make more use of this gigantic asset. The use of metadata (data about data) can clearly indicate the meaning of data on the Web so as to provide computers enough information to handle such data. On the future Web, many additional layers will be required if we want computer programs to handle the semantics (the meaning of data) properly without human - tervention. Such layers should deal with the hierarchical relationships between me- ings, their similarities and differences, logical rules for making new inferences from the existing data and metadata, and so on. Dozens of new technologies have emerged recently to implement these ideas. XML (eXtensible Markup Language) forms the foundation of the future Web, RDF (Resource Description Framework), OWL (Web Ontology Language) and many other technologies help to erect a “multistory” bui- ing of the Semantic Web layer by layer by adding new features and new types of metadata. According to Tim Berners-Lee, the inventor of the current Web and the Semantic Web, it may take up to ten years to complete the building. The new Web will be much more complex than the current one and will contain enormous amounts of metadata as well as data.

Inhaltsverzeichnis

Frontmatter

Semantic, Visual, and Technological Facets of the Second-Generation Web

Frontmatter
Chapter 1. The Concept and Architecture of the Semantic Web
Vladimir Geroimenko
Chapter 2. Information Visualization and the Semantic Web
2.5 Conclusion
The Semantic Web emphasizes that data should be machine-understandable, whereas information visualization aims to maximize our perceptional and cognitive abilities to make sense of visual-spatial representations of abstract information structures. One of the fundamental requirements of the Semantic Web is to annotate Web data with ontology to accomplish machine-understandable Web. Will they fit to work along with one another? Our illustrative example is intended to demonstrate that on the one hand, the Semantic Web can largely simplify some information visualization tasks today, and semantic annotation can be utilized for semantic visualization; on the other hand, the two fields differ from their philosophical groundings to tactical approaches to individual problems such as knowledge modeling and representation. A lot of theoretical and practical work remains to be done to find the right track for the two fields to work together harmoniously.
Lawrence Reeve, Hyoil Han, Chaomei Chen
Chapter 3. Ontology-Based Information Visualization: Toward Semantic Web Applications
3.6 Summary
This chapter has demonstrated an elegant way to visually represent ontological data. We have described how the Cluster Map visualization can use ontologies to create expressive information visualizations, with the attractive property that classes and objects that are semantically related are also spatially close in the visualization.
Another key aspect of the visualization is that it focuses on visualizing instances rather than ontological models, thereby making it very useful for information retrieval purposes.
A number of applications developed in the past few years have been described that prominently incorporate the Cluster Map visualization. Based on these descriptions, we could distinguish a number of generic information retrieval tasks that are well supported by the visualization.
These applications prove the usability and usefulness of the Cluster Map in real-life scenarios. Furthermore, these applications show the applicability of the visualization in Semantic Web-based environments, where lightweight ontologies are playing a crucial role in organizing and accessing heterogeneous and decentralized information sources.
Christiaan Fluit, Marta Sabou, Frank van Harmelen
Chapter 4. Topic Maps, RDF Graphs, and Ontologies Visualization
Bénédicte Le Grand, Michel Soto
Chapter 5. Web Services: Description, Interfaces, and Ontology
Alexander Nakhimovsky, Tom Myers
Chapter 6. Recommender Systems for the Web
6.9 Conclusion
Recommender systems already provide substantial user value by personalizing a number of sites on the Web. The Semantic Web brings forward rich opportunities for improving these interfaces, and for striking a better balance between content and collaborative personalization methods.
J. Ben Schafer, Joseph A. Konstan, John T. Riedl
Chapter 7. SVG and X3D: New XML Technologies for 2D and 3D Visualization
Vladimir Geroimenko, Larissa Geroimenko

Visual Techniques and Applications for the Semantic Web

Frontmatter
Chapter 8. Using Graphically Represented Ontologies for Searching Content on the Semantic Web
8.4 Conclusion and Further Work
As presented in this chapter, the main building blocks of the GODE are already available, though, at the time of writing, not integrated. By implementing the GODE as a plug-in for existing technology such as CORPORUM® Knowledge Server or CORPORUM® Intelligent Components, users can already get accustomed to the new way of searching to get ready for the next step: the Semantic Web. When the Semantic Web becomes more mature, plug-ins for conversion of visual queries to the various Semantic Web query languages will be made in order to make the Semantic Web as available for the general audience as the Web is today.
The Graphical Ontology Designer Environment is meant to give today’s search engine users the possibility to draw on the full use of the Semantic Web, without having to learn complex query languages. By gently introducing the presented search concept by means of a guided search, where one can type a natural language text of which a graphical ontology is created, the naive users get the opportunity to explore the Semantic Web with a low threshold. In a later phase (medium-level) users can construct their own graphical ontologies from scratch and run it through an ontology-checking algorithm to make sure the ontology is of good quality and does not contain any contradictions or “impossible” situations. Once the users have reached the expert level, they can benefit from the advanced options of the GODE and define relation types between the search concepts to retrieve even more accurate results.
Leendert W. M. Wienhofen
Chapter 9. Adapting Graph Visualization Techniques for the Visualization of RDF Data
Flavius Frasincar, Alexandru Telea, Geert-Jan Houben
Chapter 10. Spring-Embedded Graphs for Semantic Visualization
10.7 Conclusions
In this chapter we have presented a graph drawing system for visualizing ontologies and collections of instance data on the Semantic Web. Related entities are drawn close to each other with a directed edge to symbolize the relationship, and the system is also capable of producing sensible automatic layouts of disconnected graphs. Through two case studies involving a real, deployed ontology and an aggregated set of instance data, we show how patterns about the underlying structure are more easily understood through the graph drawing than through text or other types of visual displays.
Jennifer Golbeck, Paul Mutton
Chapter 11. Semantic Association Networks: Using Semantic Web Technology to Improve Scholarly Knowledge and Expertise Management
Katy Börner
Chapter 12. Interactive Interfaces for Mapping E-Commerce Ontologies
Vladimir Geroimenko, Larissa Geroimenko
Chapter 13. Back Pain Data Collection Using Scalable Vector Graphics and Geographical Information Systems
Gheorghita Ghinea, Tacha Serif, David Gill, Andrew O. Frank
Chapter 14. Social Network Analysis on the Semantic Web: Techniques and Challenges for Visualizing FOAF
John C. Paolillo, Elijah Wright
Chapter 15. Concluding Remarks: Today’s Vision of Envisioning the Semantic Future
Vladimir Geroimenko, Chaomei Chen
Backmatter
Metadaten
Titel
Visualizing the Semantic Web
herausgegeben von
Vladimir Geroimenko, DSc, PhD, MSc
Chaomei Chen, PhD, MSc, BSc
Copyright-Jahr
2006
Verlag
Springer London
Electronic ISBN
978-1-84628-290-4
Print ISBN
978-1-85233-976-0
DOI
https://doi.org/10.1007/1-84628-290-X

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