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AUDIT: approving and tracking updates with dependencies in collaborative databases

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dc.contributor.author Mershad, Khaleel
dc.contributor.author Malluhi, Qutaibah M.
dc.contributor.author Ouzzani, Mourad
dc.contributor.author Tang, Mingjie
dc.contributor.author Gribskov, Michael
dc.contributor.author Aref, Walid G.
dc.date.accessioned 2024-02-27T13:07:21Z
dc.date.available 2024-02-27T13:07:21Z
dc.date.copyright 2018 en_US
dc.date.issued 2017-09-21
dc.identifier.issn 0926-8782 en_US
dc.identifier.uri http://hdl.handle.net/10725/15345
dc.description.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. en_US
dc.language.iso en en_US
dc.title AUDIT: approving and tracking updates with dependencies in collaborative databases en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 202203388 en_US
dc.author.department Computer Science And Mathematics en_US
dc.relation.journal Distributed and Parallel Databases en_US
dc.journal.volume 36 en_US
dc.article.pages 81-119 en_US
dc.keywords Collaborative databases en_US
dc.keywords Cloud computing en_US
dc.keywords Data dependency en_US
dc.keywords Multiversion data en_US
dc.keywords Update authorization en_US
dc.keywords Big data en_US
dc.identifier.doi https://doi.org/10.1007/s10619-017-7208-y en_US
dc.identifier.ctation Mershad, K., Malluhi, Q. M., Ouzzani, M., Tang, M., Gribskov, M., & Aref, W. G. (2018). AUDIT: approving and tracking updates with dependencies in collaborative databases. Distributed and Parallel Databases, 36, 81-119. en_US
dc.author.email khaleel.mershad@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://link.springer.com/article/10.1007/s10619-017-7208-y en_US
dc.orcid.id https://orcid.org/0000-0003-3786-5529 en_US
dc.author.affiliation Lebanese American University en_US


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