THESIS
2022
1 online resource (x, 50 pages) : illustrations (chiefly color)
Abstract
Array DataBase Management Systems (ADBMSs) has recently become a promising
approach that addresses the challenges of efficient managing scientific databases and
ADBMS facilitates data-intensive project collaboration. Many ADBMSs have developed
to address the challenges derived from data-driven research. Nevertheless, there is yet no
broadly accepted standard database model for array data, thus leaving many topics to be
explored and optimized.
In this thesis, we present an efficient strategy called TravelGraph for managing versions
of an array database. Data versioning is a crucial feature for supporting scientific research
and large-scale collaborative data-intensive work. By leveraging version metadata, the
strategy facilitates better scientists’ collaboration and optimizes inter-versi...[
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Array DataBase Management Systems (ADBMSs) has recently become a promising
approach that addresses the challenges of efficient managing scientific databases and
ADBMS facilitates data-intensive project collaboration. Many ADBMSs have developed
to address the challenges derived from data-driven research. Nevertheless, there is yet no
broadly accepted standard database model for array data, thus leaving many topics to be
explored and optimized.
In this thesis, we present an efficient strategy called TravelGraph for managing versions
of an array database. Data versioning is a crucial feature for supporting scientific research
and large-scale collaborative data-intensive work. By leveraging version metadata, the
strategy facilitates better scientists’ collaboration and optimizes inter-version queries. We
transform the metadata of versions into a acyclic directed graph to demonstrate their
provenance information, and further select a set of versions to materialize in order to
fulfill the requirement which is tunable to users. The experimental results show that our
proposed strategy reduces the resource burden arising from version storage and reduces
the cost of recreating old versions.
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