Measuring Information Gain using Provenance

In recent years, a large amount of data is collected from multiple sources and the demands for analyzing these data have increased enormously. Data sharing is a valuable part of this data-intensive and collaborative environment due to the synergies and added values created by multi-modal datasets generated from different sources. In this work, we introduce a technique that can be used for quantifying the degree of information gain (IG) that may be obtained over data sharing. Our method captures both where- (to compute the IG over values) and how-provenance (to find matching records) and accurately computes the IG based on them. We conduct a preliminary evaluation to show the runtime of our approach over a real-world dataset.