Putting Things into Context: Rich Explanations for Query Answers using Join Graphs

Conference Paper

In many data analysis applications there is a need to explain why a surprising or interesting result was produced by a query. Previous approaches to explaining results have directly or indirectly relied on data provenance, i.e., input tuples contributing to the result(s) of interest. However, some information that is relevant for explaining an answer may not be contained in the provenance. We propose a new approach for explaining query results by augmenting provenance with information from other related tables in the database. Using a suite of optimization techniques, we demonstrate experimentally using real datasets and through a user study that our approach produces meaningful results and is efficient.

Full Text

Duke Authors

Cited Authors

  • Li, C; Miao, Z; Zeng, Q; Glavic, B; Roy, S

Published Date

  • January 1, 2021

Published In

Start / End Page

  • 1051 - 1063

International Standard Serial Number (ISSN)

  • 0730-8078

Digital Object Identifier (DOI)

  • 10.1145/3448016.3459246

Citation Source

  • Scopus