ViP: A user-centric view-based annotation framework for scientific data

Abstract

Annotations play an increasingly crucial role in scientific exploration and discovery, as the amount of data and the level of collaboration among scientists increase. In this paper, we introduce ViP, a user-centric, view-based annotation framework that promotes annotations as first-class citizens. ViP introduces novel ways of propagating annotations, empowering users to express their preferences over the time and network semantics of annotations. To efficiently support such novel functionality, ViP utilizes database views and introduces new caching techniques. Through an extensive experimental study on a real system, we show that ViP can seamlessly introduce new annotation propagation semantics while significantly improving the performance over the current state of the art. © 2008 Springer-Verlag.