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Explaining why an answer is (not) in the result of a query has proven to be of immense importance for many applications. However, why-not provenance, and to a lesser degree also why-provenance, can be very large, even for small input datasets. The resulting scalability and usability issues have limited the applicability of provenance. We present PUG, a system for why and why-not provenance that applies a range of novel techniques to overcome these challenges. Specifically, PUG limits provenancedoi:10.14778/3229863.3236233 fatcat:fxy3gujinbfc7jeun4gvafp7j4