iOS UI Tour

The process of finding something to read is typically framed as a process of

• Recommendation
• Browse
• Search

The process of discovery we believe always starts with recommendation. Whether a user comes to the library to search for a specific title or author, the intent is informed by some prior recommendation or suggestion regarding the work, or author. The less informed method of discovery can be guided by expert recommendation of a librarian or the user’s awareness of their book preferences through browse paths to collections of books. When users come to the library, they have ready access to librarians to assist them in their discovery. This expert extracts information from the user and guides the user to content in which they can browse collections or directs them to the particular title they are looking for. In commercial bookstores or online books stores, self-guided browsing experiences are facilitated by highly curated collections and navigation schemes and queues based on genre, appeal and popularity.

The process of borrowing a book from the library "digitally" is cumbersome. However, buying a book commercially is simple from a user perspective. This stems from online book stores having an unlimited supply. Libraries have forced scarcity and must elegantly deal with this issue. To reduce the complexity, we remove the choices from this transaction stream. First, we standardize packaging (EPUB3) and remove alternate digital format decisions. Second, automatically eliminate transaction options if they are irrelevant and only present options and information needed. Third, allow users to "shop" before executing a check requirement (e.g. entering their library card if or signing in.)

The reading of experience for libraries in regards to eBooks is not unlike that of commercial applications. However, we believe that pure consumption of the content over the user's interaction with the content should be better facilitated. This requires adoption of EPUB3. The EPUB3 format requires additional media types beyond text to be exposed to the readers such as audio, video, and Math ML to be displayed. Additionally, users may want to comment or highlight and annotate content they are researching, referencing or sharing with others. Social features are important for building readers communities and recommending content.