Features
From WandoraWiki
(Difference between revisions)
| Line 30: | Line 30: | ||
** [[MediaWiki extractor|Convert MediaWiki pages to a topic map]] | ** [[MediaWiki extractor|Convert MediaWiki pages to a topic map]] | ||
** [[Audioscrobber extractors|Convert Last.fm XML feeds to a topic map]] | ** [[Audioscrobber extractors|Convert Last.fm XML feeds to a topic map]] | ||
| + | * Analyze topic maps | ||
| + | ** Clustering coefficient for any topic set including average clustering coefficient of a topic map. | ||
| + | ** Topic map diameter and average path length. | ||
| + | ** Topic map connection count and distribution (Topic map degree distribution). | ||
* Tools to publish knowledge | * Tools to publish knowledge | ||
** [[Exporting WWW site|Export the topic map as a collection of static HTML pages]] | ** [[Exporting WWW site|Export the topic map as a collection of static HTML pages]] | ||
| Line 36: | Line 40: | ||
** Download and manage subject locator files | ** Download and manage subject locator files | ||
** Build your own topic map application using the [[Wandora Web Service]] interface | ** Build your own topic map application using the [[Wandora Web Service]] interface | ||
| + | * Generate simple topic map graphs. | ||
| + | ** Random graph generator. | ||
| + | ** Fully connected graph generator. | ||
| + | ** Tree graph generator. | ||
| + | ** Linear list graph generator. | ||
| + | ** Finite group graph generator. | ||
* Plugin architecture makes it easy to add custom functionality | * Plugin architecture makes it easy to add custom functionality | ||
** Tools that process topic map, for example cleaning or reconstructing data | ** Tools that process topic map, for example cleaning or reconstructing data | ||
Revision as of 13:44, 4 June 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
- 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
- Convert MediaWiki pages to a topic map
- Convert Last.fm XML feeds to a topic map
- Analyze topic maps
- Clustering coefficient for any topic set including average clustering coefficient of a topic map.
- Topic map diameter and average path length.
- Topic map connection count and distribution (Topic map degree distribution).
- 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
- Build your own topic map application using the Wandora Web Service interface
- Generate simple topic map graphs.
- Random graph generator.
- Fully connected graph generator.
- Tree graph generator.
- Linear list graph generator.
- Finite group graph generator.
- 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
