Abstract:
In the era of big data where every individual is a target of intensive data collection, there is a
need to create technological tools that empower individuals to track what happens to their data.
Provenance has been studied extensively in both database and workow management systems,
so far with little focus on text-retrieval based workows with user defined operators. Such kind
of workow provenance aims to capture a complete description of evaluation (or enactment)
of a workow, and this is crucial to this problem of personal data use. As an initial step to
solving this problem, the work presented in this report aims at developing our own tamper proof
temporal provenance storage platform and query based model that can track, store and analyze
data transformations.
