One of the most amazing aspects of this new digital world we live in is the sheer quantity of information and media that we are able to access inside applications, on our laptops and devices, and on networks and the Internet. Unfortunately, accompanying the boundless possibilities of this access is a hard design problem: How do we make it easy for people to find what they’re looking for, and more importantly, find what they need?
Fortunately, great strides have been made in this area by the likes of Google, with its various search engines, and Apple, with its highly effective Spotlight functionality in Mac OS X (more on these later). However, although these solutions certainly point to effective interactions, they are just a start. Just because Google is a very useful way to find textual or video content on the Web, doesn’t mean that the same interaction patterns are appropriate for a more targeted retrieval scenario.
As with almost every other problem in interaction design, we’ve found that crafting an appropriate solution must start with a good understanding of users’ mental models and usage contexts. With this information, we can structure storage and retrieval systems that accommodate specific purposes. This chapter discusses methods of data retrieval from an interaction standpoint and presents some human-centered approaches to the problem of finding useful information.
A storage system is ...