Ziggy: Characterizing Query Results for Data Explorers

Summary: Ziggy identifies characteristic views—small column subsets where result tuples differ from the rest of the database—to help data explorers understand their results. It complements exploration systems by exposing why a selection is unique, guiding iterative refinement. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11260
Venue: VLDB
Year: 2016
Pagerank: 4.3138911e-05
Overall Rank: 9,630 | 33.01%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Thibault Sellam
2. Martin Kersten

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,344	Exploring the Data Wilderness through Examples	2019	SIGMOD	4.5428111e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,152	Blink and It's Done: Interactive Queries on Very Large Data	2012	VLDB	0.00013645792

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