Semantics in Wiki - Community-Built Databases: Research and Development - page 250

easy-to-use inline wiki annotations and various search and export functions. In
contrast to SMW, both systems introduce the concept of ontologies and (to some
extent) URIs into the wiki, which emphasises use-cases of collaborative ontology
editing that are not the main focus of SMW.
SMW has many advantages when compared with other semantic wiki engines.
The reason is that it is built on open-source MediaWiki, which has a large user
community, a mature system framework and various extensions. More importantly,
another advantage is that MediaWiki is flexible and can be easily extended for
specific use. SMW enables users to annotate the wiki's contents with explicit,
machine-readable information [ 15 ]. SMW was chosen because of its robustness,
flexibility and support [ 21 ].
According to Zou and Fan [ 21 ], all content in SMW is structured by wiki pages.
Each page could be considered a resource, a property or an individual. Pages could
be further classified into namespaces to distinguish different types of pages. Each
wiki page also has a unique name which can be treated as its URI in combination
with namespaces.
10.4.3 Why Semantic MediaWiki
Semantic MediaWiki introduces some additional markup into the wiki-text which
allows users to add “semantic annotations” to the wiki. These simplify the structure
of the wiki, help users to find more information in less time and improve the overall
quality and consistency of the wiki. Some of the benefits of using SMW are [ 2 ]:
l Automatically generated lists
l Visual display of information
l Improved data structure
l Searching information
l Inter-language consistency
l External reuse
l Integrate and mash-up data
Semantic Wikis enhance collaboration and information sharing by providing
capabilities such as:
l Concept-based rather than language-based searching: queries span vocabularies,
languages and search engines.
l Question answering rather than simple retrieval. Also, overlay ontologies and
knowledge bases can integrate with major Web searching engines.
l More richly structured content navigation, including multiple perspectives,
multiple levels of abstraction, dependency/contingency relationships, etc.
l Easy visualisation of content structure (categories, taxonomies, semantic nets, etc.).
l Direct editing of content structure.
l Mining of semantic relationships in content.