Features

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Brief introduction to the most interesting features of Wandora:
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This page summarizes perhaps the most fundamental features of Wandora application.
  
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* Graphical user interface
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== Desktop application ==
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** Topic map browser
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** Extensive collection of tools to manipulate topics and associations
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* Fast and reliable
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* [[Layered Topic Map|Layered representation of knowledge]]
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* Requires Java
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** Construct the knowledge using several different layers, each containing only part of the knowledge
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** You can view only parts of data and hide parts that don't intrest you
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== Graphical user interface ==
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** Automatic merging of different and even distributed data sources
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** Protect some parts of topic map by allowing only read access
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* [[Traditional topic panel|Topic map browser]]
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* Several data storage options
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* [[Graph topic panel|Graph visualization of a topic map]]
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** Memory based topic map for very fast processing of relatively small topic maps
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* [[Treemap topic panel|Treemap visualization]] of topics
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** Relational database storage makes it possible to use topic maps of virtually unlimited size
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* [[Webview|Embedded WWW browser]]
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** Relational database storage enables easy usage of remote third party topic maps
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* Build your own interactive visualizations using [[Processing topic panel|embedded Processing language]].
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* Import data in several formats
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** [[How to import existing topic map to Wandora|Imports topic maps in XTM and LTM formats]]
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== [[Introduction to Layered Topic Maps|Layered storage of knowledge]] ==
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** [[Importing RDF(S)|Imports RDF data in RDF(S) and N3 formats]]
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** [[Importing XML with XSL|Imports any valid XML document can be transformed to XTM with proper XSL]]
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* Supports multilayered networks
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** [[Generic SQL database import|Converts and imports any SQL database to a topic map]]
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* Construct the knowledge using several different layers, each containing only part of the knowledge
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** [[Transferring data with clipboard|Clipboard import and export of topics and associations]]
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* You can view only parts of data and hide parts that don't interest you
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* Read metadata from different file types
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* Automatic merging of different and even distributed data sources
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** [[MP3 ID3v1 and ID3v2 extractor|Convert MP3 ID3 metadata to a topic map]]
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* Protect some parts of topic map by allowing only read access
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** Convert Adobe Photoshop JPEG metadata to a topic map
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* Use nested layer stacks to create tree like layer structures
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** Convert PDF metadata to a topic map
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** [[Email extractor|Convert emails and email repositories to a topic map]]
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== Several data storage options ==
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** [[File system extractor|Convert file system structures to a topic map]]
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** [[HTML link extractor|Convert HTML site structure to a topic map]]
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* [[Memory topic map|Memory based topic map]] for very fast processing of relatively small topic maps
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** [[IMDB extractor|Convert IMDB datafiles to a topic map]]
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* [[Database topic map|Database storage]] makes it possible to use topic maps of virtually unlimited size
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* Tools to publish knowledge
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** [[Exporting WWW site|Export the topic map as a collection of static HTML pages]]
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== Import data in several formats ==
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** Create and export Lucene search index from any topic map
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** [[Setting up Wandora Piccolo server|Set up a dynamic WWW site based on the topic map with Wandora-Piccolo combination]]
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* [[How to import existing topic map to Wandora|Imports topic maps in XTM, LTM, and JTM formats]]
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** Download and manage subject locator files
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* [[Importing RDF|Imports RDF data in RDF, N3, Turtle and JSON-LD formats]]
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* Plugin architecture makes it easy to add custom functionality
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* [[OBO flat file import|Imports OBO flat file format ontologies]] such as [http://www.geneontology.org The Gene Ontology]
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** Tools that process topic map, for example cleaning or reconstructing data
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* [[Importing XML with XSL|Imports any valid XML document with proper XSL converting the XML to XTM]]
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** Importing data in different formats, for example from existing relational database
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* [[Transferring data with clipboard|Clipboard import and export of topics and associations]]
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** Exporting data in different formats
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** Reading and automatic processing of metadata from a collection of files
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== Extract topic maps from various sources ==
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** Customized ways to represent the data in the topic map
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** Custom publishing methods
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Over 50 different data format and web service extractors. Including
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* [[MP3 ID3v1 and ID3v2 extractor]]
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* [[JPG binary metadata extractor]]
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* [[PDF extractor]]
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* [[Email extractor]]
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* [[File system extractor]]
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* [[HTML link extractor]]
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* [[IMDB extractor]]
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* [[FreeDB extractor]]
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* [[Wikipedia extractor]] and more general [[MediaWiki extractor]]
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* [[Last.fm extractors]]
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* [[Bibtex extractor]]
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* [[RIS extractor]]
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* [[Simple Text Document Extractor]]
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* [[RSS 2.0 Extractor]]
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* [[Atom extractor]]
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* [[Any23 extractor|Any23 integration]]
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* [[Flickr extractors]]
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* [[YouTube extractor]]
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* [[OpenCalais classifier]]
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* [[OpenCyc extractor]]
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* [[Geonames extractors]]
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* [[SKOS RDF extractor]]
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* [[Dublin Core RDF extractor]]
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* [[FOAF RDF extractor]]
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* [[Gellish ontology extractor]]
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* [[Subj3ct record extractor]]
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* [[DBpedia extractor]]
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* [[Facebook Graph extractor]]
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* [[Twitter extractor]]
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* [[SPARQL extractor]]
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And many more...
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== Search and analyze topic maps ==
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* Search topics with regular expressions, [[Finding a topic|find similar topics]].
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* Supports [[TMQL]] (Topic Map Query Language).
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* Wandora specific [[Query language|query language]].
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* [[Compare topic maps]].
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* [[Clustering coefficient]] for any topic set including average clustering coefficient of a topic map.
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* [[Topic map diameter]] and average path length.
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* [[Topic map connection statistics|Topic map connection count and distribution]] (Topic map degree distribution).
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* [[SOM classifier]] to analyze topics with associations.
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* [[R in Wandora|R language integration]] makes Wandora a data source for R environment.
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== Export and publish ==
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* Wandora can export topic maps in XTM, LTM and JTM format.
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* [[Exporting WWW site|Export topic map as a collection of static HTML pages]].
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* Export topic maps as [[Graph Modeling Language export|Graph Modeling Language]], [[GraphML export|GraphML]], and [[GraphXML export|GraphXML]] graphs.
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* [[Embedded HTTP server]] allows you to publish topic maps as a dynamic HTML site, RSS feed or pretty much anything if you just write suitable templates for your output.
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** Included outputs: HTML, RSS instance feed, ATOM topic, Wandora Web Service.
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** We have created several [[Wandora Drupal extras]] to show you examples how Wandora can be used together with Drupal content management system.
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** We have also created [[Wandora's Joomla Topic Reader|an extra for Joomla content management system]] to demonstrate how to publish Wandora content in Joomla sites.
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** Build your own topic map application using [[Wandora Web Service|Wandora's Web Service]].
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** You can also create new output modules to Wandora easily. See chapter '''Setting up new services''' at [[Embedded HTTP server]].
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* [[Setting up Wandora Piccolo server|Wandora Piccolo combination allows you to set up a large scale dynamic WWW site based on the topic maps]].
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== Edit topic maps ==
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Wandora contains a huge collection of topic map editing features. You can not only edit topics and associations directly but also transform topic's internal structures -- such as occurrences to other structures -- such as variant names. You can also choose to apply editing feature to not just one topic but a collection of topics which speeds up topic map refactoring substantially. See Wandora's [[Documentation|documentation]] for details.
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== Generate simple topic map graphs ==
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* [[Random graph generator]]
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* [[Fully connected graph generator]]
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* [[Tree graph generator]]
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* [[Linear list graph generator]]
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* [[Finite group graph generator]]
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* [[Platonic solid graph generator]]
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* [[Hypercube graph generator]]
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* [[Tiling graph generator]]
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* [[Edge generator]]
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* [[L-system generator|Generate topic maps with L-systems]].
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== [[Tool manager|Plugin architecture makes it easy to add custom functionality]] ==
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* Tools that process topic map, for example cleaning or reconstructing data
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* Importing data in different formats, for example from existing relational database
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* Exporting data in different formats
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* Reading and automatic processing of metadata from a collection of files
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* Customized ways to represent the data in the topic map
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* Custom publishing methods
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Now you might want to continue to
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* Wandora [[Download]]
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* View Wandora [[Screenshots]]
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* Browse Wandora's [[Documentation]]
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__NOTOC__

Latest revision as of 14:43, 31 July 2015

This page summarizes perhaps the most fundamental features of Wandora application.

[edit] Desktop application

  • Fast and reliable
  • Requires Java

[edit] Graphical user interface

[edit] Layered storage of knowledge

  • Supports multilayered networks
  • 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 interest you
  • Automatic merging of different and even distributed data sources
  • Protect some parts of topic map by allowing only read access
  • Use nested layer stacks to create tree like layer structures

[edit] Several data storage options

[edit] Import data in several formats

[edit] Extract topic maps from various sources

Over 50 different data format and web service extractors. Including

And many more...

[edit] Search and analyze topic maps

[edit] Export and publish

[edit] Edit topic maps

Wandora contains a huge collection of topic map editing features. You can not only edit topics and associations directly but also transform topic's internal structures -- such as occurrences to other structures -- such as variant names. You can also choose to apply editing feature to not just one topic but a collection of topics which speeds up topic map refactoring substantially. See Wandora's documentation for details.

[edit] Generate simple topic map graphs

[edit] 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


Now you might want to continue to


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