(via http://uxbasis.hellogroup.com and http://userpathways.com)

Last summer i worked at Yahoo! as an interaction design intern and my major summer project was to design the new Information Architecture for the Pattern Library. Today the Yahoo! Design Pattern Library was relaunched with a new face – more open and social. It includes 10 new Social Patterns, a reorganized category-structure, cleaner URLs for easier bookmarking and much more.

Come and check it out at http://design.yahoo.com

The collection of ratings happens either in itunes upon downloading an application as well as on the phone after removing the application. This creates a very biased environment for rating applications. Most ratings will be the result of uninstalling an app and not necessarily give a realistic representation of votes as it does not capture or distinguish between a crappy app or an app that just did not meet the user’s expectations. To solve this issue i suggest to make it more clear that the collected rating is reflecting the quality of the application rather than maybe just downloading it with the wrong expectations.

On the other hand i suggest that Apple uses quantitative data about application usage to generate more accurate ratings. The following metrics could be used to verify the quality and usefulness of applications assuming that frequency of use is a major characteristic and contributing factor for users to decide if an installation is worth it.

• Age -Duration how long the app has been installed
• Active – Total time the app has been running since installation
• Times Started – Number of times the app has been opened by the user
• Times Started (last week) – Number of times within the last 7 days
• Position (absolute) – Position of app icon, counted starting in top left corner on first page
• Position (page) – On which page the app icon is placed
• Push Notifications – how many notifications have been send by the application
• Push Notifications (last week) – Notifications within the last week

There are no good tools that make these patterns usable, and there isn’t much community to speak of around them. We at Infragistics thought that we could help and fill the gap – helping to make UX design patterns more findable, more discoverable, more usable, and, we hope, more communal and social.

These taste preference can be categorized into “never, sometimes and often” and are supported by six example movies to understand what netflix considers to be classified under the mood. These can be changed later on.