AUDIT: approving and tracking updates with dependencies in collaborative databases

Khaleel Mershad*, Qutaibah M. Malluhi, Mourad Ouzzani, Mingjie Tang, Michael Gribskov, Walid G. Aref

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Collaborative databases such as genome databases, often involve extensive curation activities where collaborators need to interact to be able to converge and agree on the content of data. In a typical scenario, a member of the collaboration makes some updates and these become visible to all collaborators for possible comments and modifications. At the same time, these updates are usually pending the approval or rejection from the data custodian based on the related discussion and the content of the data. Unfortunately, the approval and authorization of updates in current databases is based solely on the identity of the user, e.g., via the SQL GRANT and REVOKE commands. In this paper, we present a scalable cloud-based collaborative database system to support collaboration and data curation scenarios. Our system is based on an Update Pending Approval model. In a nutshell, when a collaborator updates a given data item, it is marked as pending approval until the data custodian approves or rejects the update. Until then, any other collaborator can view and comment on the data, pending its approval. We fully realized our system inside HBase, a cloud-based platform. We also conducted extensive experiments showing that the system scales well under different workloads.

Original languageEnglish
Pages (from-to)81-119
Number of pages39
JournalDistributed and Parallel Databases
Volume36
Issue number1
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • Big data
  • Cloud computing
  • Collaborative databases
  • Data dependency
  • Multiversion data
  • Update authorization

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