Association for Computing Machinery
In this paper, the authors address the challenges that arise from the growing scale of annotations in scientific databases. On one hand, end-users and scientists are incapable of analyzing and extracting knowledge from the large number of reported annotations, e.g., one tuple may have hundreds of annotations attached to it over time. On the other hand, current annotation management techniques fall short in providing advanced processing over the annotations beyond just propagating them to end-users. To address this limitation, they propose the InsightNotes system, a summary-based annotation management engine in relational databases.