Features
From WandoraWiki
(Difference between revisions)
| Line 32: | Line 32: | ||
* Analyze topic maps | * Analyze topic maps | ||
** [[Clustering coefficient]] for any topic set including average clustering coefficient of a topic map. | ** [[Clustering coefficient]] for any topic set including average clustering coefficient of a topic map. | ||
| − | ** Topic map diameter and average path length. | + | ** [[Topic map diameter]] and average path length. |
| − | ** Topic map connection count and distribution (Topic map degree distribution). | + | ** [[Topic map connection statistics|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 41: | Line 41: | ||
** Build your own topic map application using [[Wandora Web Service|Wandora's SOAP Web Service]] | ** Build your own topic map application using [[Wandora Web Service|Wandora's SOAP Web Service]] | ||
* Generate simple topic map graphs. | * Generate simple topic map graphs. | ||
| − | ** Random graph generator | + | ** [[Random graph generator]] |
| − | ** Fully connected graph generator | + | ** [[Fully connected graph generator]] |
| − | ** Tree graph generator | + | ** [[Tree graph generator]] |
| − | ** Linear list graph generator | + | ** [[Linear list graph generator]] |
| − | ** Finite group 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 18:25, 15 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 Wandora's SOAP Web Service
- Generate simple topic map graphs.
- 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
