TY - JOUR
T1 - AUDIT
T2 - approving and tracking updates with dependencies in collaborative databases
AU - Mershad, Khaleel
AU - Malluhi, Qutaibah M.
AU - Ouzzani, Mourad
AU - Tang, Mingjie
AU - Gribskov, Michael
AU - Aref, Walid G.
N1 - Publisher Copyright:
© 2017, Springer Science+Business Media, LLC.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - 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.
AB - 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.
KW - Big data
KW - Cloud computing
KW - Collaborative databases
KW - Data dependency
KW - Multiversion data
KW - Update authorization
UR - http://www.scopus.com/inward/record.url?scp=85029671084&partnerID=8YFLogxK
U2 - 10.1007/s10619-017-7208-y
DO - 10.1007/s10619-017-7208-y
M3 - Article
AN - SCOPUS:85029671084
SN - 0926-8782
VL - 36
SP - 81
EP - 119
JO - Distributed and Parallel Databases
JF - Distributed and Parallel Databases
IS - 1
ER -