Information Visualisation and the Semantic Web
The Semantic Web is a new research mainstream started on a vision of Tim Berners-Lee in 1998. The main idea of the Semantic Web is to take advantage of the huge quantity of information provided by the Web and make it available into a format “understandable” to computer programs. Documents on the web are mainly encoded in HTML format, which was created to present information to human readers thought a Web browser. This format specify how the layout of a paragraph, or a part of a text, must be presented to the users: fonts, colors, align, etc. Nothing about the “semantic” of a text is encoded in an HTML file (e.g. there are not tag that specify who is the author of a document). Only humans are able to hunderstand the content of a rendered HTML pages.
The Semantic Web moves a step forward, aims to build the content of web sites in a meningful way that it would be understandable not only to human beings, but also to computers. This can be achieved by technologies that use XML derived languages to encode the content of documents in Internet, such as RDF (resource description framework) and Topic Maps that add computer-understandable meanings that describe the data (the metadata). With ontologies (mechanisms for representing the description of a domain, encoded in RDF or similar technlogies), computer programs can exchange information with a shared semantic of his meaning.
“IV aims to produce graphical representations of abstract information structure for human users, whereas the Semantic Web aims to rely on a universal descriptive framework of resources that can be utilized by software agents. … the two research fields differ in some fundamental ways in terms how semantics is defined and represented” [geroimenko:semanticwebinfo:03, p. 15]. However, some applications of Semantic Webs may take advantage of the semantics provided by ontologies and viceversa. In the following paragraph we will describe some applications where the Semantic Web could be effectively coupled with some graphical representations.
The FRODO RDFSViz  and OntoViz are two examples of applications that aim to visualise ontologies represented in RDF Schema (FRODO RDFSViz) and ontologies represented with Topic Maps (OntoViz).
The Persons and Competencies (PeC) Navigator is an application which aims to visualize, navigate, and search resources representing persons, groups of persons and competencies within organizations. Data are stored in RDF files and an ontology defined in the OWL language represents persons, groups, competence elements and the relationships among them, such as “knows”among people and a competence, or “isMemberOf” among people and groups. The image below shows an example of graphic visualization of human resources and groups, and all their related competencies within the Organization.
Links to other tools
- RDF Gravity (RDF Graph Visualization Tool),
- ontosphere3d, http://ontosphere3d.sourceforge.net/userGuide.html
- OntoViz, http://protegewiki.stanford.edu/index.php/OntoViz
- Ontology Browser
- Serguei Krivov, Ferdinando Villa, Richard Williams and Xindong Wu, ON VISUALIZATION OF OWL ONTOLOGIES.
- AKRIVI KATIFORI, CONSTANTIN HALATSIS, GEORGE LEPOURAS, COSTAS VASSILAKIS, EUGENIA GIANNOPOULOU. Ontology Visualization Methods – A Survey.
Information Visualisation in Data Mining
Visual data mining combines human visual perception and recognition capabilities with computationa systems for the exploration of large data sets.
A special number of the journal of Universal Computer Science  has been published on this theme
- Visualisation of conversations: See M. Hearst coursenote 2002
- BlogViz – Visualization of conversations in blogs. http://www.blogviz.com