Approving updates in collaborative databases

Abstract

Data curation activities in collaborative databases mandate that collaborators interact until they converge and agree on the content of their data. Typically, updates by a member of the collaboration are made visible to all collaborators for comments but at the same time are pending the approval or rejection of the data custodian, e.g., the principal scientist or investigator (PI). In current database technologies, approval and authorization of updates is based solely on the identity of the user, e.g., via the SQL GRANT and REVOKE commands. However, in collaborative enviroments, the updated data is open for collaborators for discussion and further editing and is finally approved or rejected by the PI based on the content of the data and not on the identity of the updater. In this paper, we introduce a cloud-based collaborative database system that promotes and enables collaboration and data curation scenarios. We realize content-based update approval and history tracking of updates inside HBase, a distributed and scalable open-source cluster-based database. The design and implementation as well as a detailed performance study of several approaches for update approval are presented and contrasted in the paper.