Tag
Problem summary
The user wants to find more data in the same category and/or contribute data in the same category
Example
Usage
- Use when the content on your website is possibly mapped into multiple categories and does not necessarily only fit into one hierarchical category.
- Use when you want users to contribute data to your website and let them organize their contributed data themselves.
Solution
Let the contributers of information on your website add keywords (tags) to the content they submit. These keywords are then transformed into links that leads to tag pages; listing all other contributions for that tag (category).
Rationale
Tags are relevant keywords associated with or assigned to a piece of information. Tags are often used on social websites, where users can upload their own content. Here, tags are used to let users organize and categorize their own data in the public sphere. In this way, tags can be seen as a bottom-up categorization of data rather than a top-down categorization of data, where the creators of the site define the hierarchy data is submitted to.
More examples images of the Tag pattern
 |
 |
 |
| Tags added to a blog post. | When adding tags at flickr, you can choose from tags you gave other pictures (grayed out) or type new. Upon submission, each tag is shown above the input field in a vertical list. They can each be easily removed separately. | When adding tags to a video at Vimeo, tags are separated by commas, and each tag are upon submission added to a horizontal line below the input field. Each tag can easily be removed separately. |
“Tags are relevant keywords associated with or assigned to a piece of information.” The problem is, who chooses when a certain tag ís indeed relevant and when it isn’t. Using the tag “css” for every article that has the word css in it might just result in 300 articles with the same tag attached to it. But if we only take those articles that are specifically about css, we might get a nice small list, containing for css articles, but not the one I was looking for. A Google like search system, based on clicks for example, and a well chosen list of “relevant articles”, maybe supported by “other people who liked this article also liked this and that”, will do the job better. I don’t like tags.