JabberWocky: Crowd-Sourcing Metadata for Files

Finding relevant files in a personal file system continues to be a challenge. It is still easier to find stuff on the Web with its exponential growth than in one´s personal file system. Yet, the exponential growth of personal data renders the current services of personal file systems increasingly inadequate. A reason for this failure is the ldquocold-startrdquo problem: algorithms that dramatically improve a user´s ability to find documents on the Web become ineffective in personal file systems because there is not enough information about these documents. We propose JabberWocky, a service that allows users to manage the content of their personal file system by leveraging semantic relationships available on the Web. More specifically, JabberWocky is using keyword/resource associations of social bookmarking web sites as a basis for recommending keywords for files. We chose social bookmarking web sites because of their popularity and because the assignment of keywords (a process also referred to as ldquotaggingrdquo) is an established and popular way to manage photos, music, movies, and audio resources on the Web - very much the kind of resources that need to be managed in personal file systems. The goal of JabberWocky is to overcome the ldquocold-startrdquo problem of personal file systems and to provide recommendations in a scalable way while maintaining the user´s privacy. In this work-in-progress report we describe the motivation and challenges of designing a system like JabberWocky, present the initial design of an on-going user study, and briefly discuss what we have learned so far.