For those of us interested in collaborative knowledge development, the fast development of TermWiki is impressive. The site (
www.termwiki.com) has been online for only seven months, but it has already accumulated more than 650K terms. TermWiki's speed of growth is much faster than that of Wikipedia in its early days. This fast development owes much to TermWiki's unusual but highly efficient data organization combined with the wiki-based collaboration model. Unlike Wikipedia which contains mostly flat data, i.e. text spread out on a page without any particular order, TermWiki uses only structured data organized into a set of pre-defined attributes or meta tags. This means every piece of text on
TermWiki belongs to a database entry, so it can be easily indexed, searched and translated.
For example, if you search a term for digital cameras with TermWiki, the search results are only pulled from content in the consumer electronics industry and for digital cameras. Why is this industry association important? The biggest benefit is that people can find information they need with better accuracy and speed. The web is full of flat and unorganized information. This is why if you enter a word into a search engine such as Google, you are likely to get thousands of search results. The reason is that search engines can only index word patterns and phrases without accurately knowing the subject matter field of the surrounding content. Although meta tags and keywords can shed some light, they are mostly on a page or site level, so there is no way to precisely pinpoint the target field of each term.
As the web continues to gather information exponentially, the situation can only get worse as the number of search results explode further making it difficult for users to find target information quickly. A recent study by the analyst firm Forrester Research found that information on the web is 10 times more powerful if it is organized based on subject relevance. TermWiki does just this. It enforces strict classifications of each term by industry/domain, product category and products. Over time, this will prove invaluable as it builds up its data collection.
By contrast, Wikipedia does not support explicit domain classifications for each term. Instead, it piles the same page with text to explain each scenario and usage examples.
Another important advantage of TermWiki's unique term classification is that the site is easily translated into all other languages by significantly reducing ambiguity and downright mistakes. The strict data categorization allows more accurate translations as each term can be precisely translated based on the industry and context information. For example, the word "block" can mean one thing in sports, and another in automotive and say mobile communications. For enhanced (machine) translation and localization quality, it's crucial to distinguish the context in order to obtain the precise meaning.
It’s worth noting that Wikipedia does present information about a term in its entirety including extra background descriptions along with each synonym scenario and definitions, making the site useful for linguists and academics conducting subject matter research. Conversely, TermWiki explains each term in a short and concise manner, appealing to everyday users who are simply for the meaning of a concept quickly.
Finally, perhaps the biggest difference between Wikipedia and TermWiki is the treatment of the contributors. TermWiki tries to give its contributors more visibility with the use of an eBay like user profile. For the social networking conscious crowd, this feature may prove beneficial as it allows users to get connected with friends as well as a chance to market their own products and services.
More Information:Both Wikipedia and
TermWiki will continue to be highly useful sources of information. In the long run, however, the quality of data and
foreign language support will be the key for each site to be successful globally.
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