Features

Revision as of 10:59, 2 May 2007

Brief introduction to the most interesting features of Wandora:

• Graphical user interface
  • Topic map browser
  • Extensive collection of tools to manipulate topics and associations
• Layered representation of knowledge
  • Construct the knowledge using several different layers, each containing only part of the knowledge
  • You can view only parts of data and hide parts that don't intrest you
  • Automatic merging of different and even distributed data sources
  • Protect some parts of topic map by allowing only read access
• Several data storage options
  • Memory based topic map for very fast processing of relatively small topic maps
  • Relational database storage makes it possible to use topic maps of virtually unlimited size
  • Relational database storage enables easy usage of remote third party topic maps
• Import data in several formats
  • Imports topic maps in XTM and LTM formats
  • Imports RDF data in RDF(S) and N3 formats
  • Imports any valid XML document with proper XSL converting the XML to XTM
  • Converts and imports any SQL database to a topic map
  • Clipboard import and export of topics and associations
• Read metadata from different file types
  • Convert MP3 ID3 metadata to a topic map
  • Convert JPEG metadata to a topic map
  • Convert PDF metadata to a topic map
  • Convert emails and email repositories to a topic map
  • Convert file system structures to a topic map
  • Convert HTML site structure to a topic map
  • Convert IMDB datafiles to a topic map
  • Convert freedb database entries to a topic map
  • Converts MediaWiki pages to a topic map
• Tools to publish knowledge
  • Export the topic map as a collection of static HTML pages
  • Create and export Lucene search index from any topic map
  • Set up a dynamic WWW site based on the topic map with Wandora-Piccolo combination
  • Download and manage subject locator files
• Plugin architecture makes it easy to add custom functionality
  • Tools that process topic map, for example cleaning or reconstructing data
  • Importing data in different formats, for example from existing relational database
  • Exporting data in different formats
  • Reading and automatic processing of metadata from a collection of files
  • Customized ways to represent the data in the topic map
  • Custom publishing methods