Finding Convincing Views to Endorse a Claim

Summary: Reverse task: find significant, “natural” selection views that convincingly support or rebut a given aggregate-comparison claim, exposing potential cherry-picking. Propose multiple naturalness measures and anytime two-stage algorithms—rank attribute combinations with cheap features, then efficiently search views—and validate quality, cost, and usability experimentally and via a user study. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14054
Venue: VLDB
Year: 2025
Pagerank: 4.1905499e-05
Overall Rank: 10,747 | 25.31%
DOI: 10.14778/3705829.3705857

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,140	Analyzing Deviations from Monotonic Trends through Database Repair	2026	SIGMOD	4.1905499e-05
10,147	Causal Explanations for Disparate Trends: Where and Why?	2026	SIGMOD	4.1905499e-05
10,213	Stress-Testing Causal Claims via Cardinality Repairs	2026	SIGMOD	4.1905499e-05
10,814	ClaimIt: Finding Convincing Views to Endorse a Claim	2025	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 35 of 35 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
213	Scorpion: Explaining Away Outliers in Aggregate Queries	2013	VLDB	0.0003371037
247	On the Computation of Multidimensional Aggregates	1996	VLDB	0.00030923842
461	SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics	2015	VLDB	0.00022615628
487	Why Not?	2009	SIGMOD	0.00022030123
943	A Formal Approach to Finding Explanations for Database Queries	2014	SIGMOD	0.00015140995
1,001	Intelligent Rollups in Multidimensional OLAP Data	2001	VLDB	0.00014709145
1,096	Interpretable and Informative Explanations of Outcomes	2015	VLDB	0.00014088686
1,119	The Complexity of Causality and Responsibility for Query Answers and non-Answers	2011	VLDB	0.00013851012
1,830	Relaxing Join and Selection Queries	2006	VLDB	0.0001037611
1,869	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	0.00010263235
2,400	Causality and Explanations in Databases	2014	VLDB	8.884178e-05
2,511	ClaimBuster: The First-ever End-to-end Fact-checking System	2017	VLDB	8.6177955e-05
2,600	Tracing Data Errors with View-Conditioned Causality	2011	SIGMOD	8.4652308e-05
2,655	Explaining Query Answers with Explanation-Ready Databases	2016	VLDB	8.3638668e-05
2,816	Bias in OLAP Queries: Detection, Explanation, and Removal (Or Think Twice About Your AVG-Query)	2018	SIGMOD	8.0747683e-05
2,925	Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals	2021	SIGMOD	7.8877522e-05
3,343	Toward Computational Fact-Checking	2014	VLDB	7.196079e-05
3,542	Extracting Top-K Insights from Multi-dimensional Data	2017	SIGMOD	6.9896948e-05
3,687	On Detecting Cherry-picked Trendlines	2020	VLDB	6.8376481e-05
3,820	Promotion Analysis in Multi-Dimensional Space	2009	VLDB	6.7266035e-05
4,819	Scrutinizer: Fact Checking Statistical Claims	2020	VLDB	5.8951e-05
5,192	Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances	2019	SIGMOD	5.6324589e-05
5,193	QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data	2019	SIGMOD	5.6322426e-05
5,321	XInsight: eXplainable Data Analysis Through The Lens of Causality	2023	SIGMOD	5.5676564e-05
5,428	High-Level Why-Not Explanations using Ontologies	2015	PODS	5.5125084e-05
5,706	Putting Things into Context: Rich Explanations for Query Answers using Join Graphs	2021	SIGMOD	5.3633001e-05
6,644	Query Refinement for Diversity Constraint Satisfaction	2024	VLDB	4.973836e-05
7,200	Guided Exploration of Data Summaries	2022	VLDB	4.7980895e-05
7,262	HypDB: A Demonstration of Detecting, Explaining and Resolving Bias in OLAP queries	2018	VLDB	4.7811818e-05
7,730	AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets	2019	VLDB	4.6613872e-05
8,388	FEDEX: An Explainability Framework for Data Exploration Steps	2022	VLDB	4.525436e-05
9,768	DPXPlain: Privately Explaining Aggregate Query Answers	2023	VLDB	4.2815042e-05
10,814	ClaimIt: Finding Convincing Views to Endorse a Claim	2025	VLDB	4.1905499e-05
11,395	OREO: Detection of Cherry-picked Generalizations	2022	VLDB	4.1905499e-05
11,422	On Detecting Cherry-picked Generalizations	2022	VLDB	4.1905499e-05

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8,288	View Selection over Knowledge Graphs in Triple Stores	2021	VLDB	4.5392079e-05
2,936	Answering Top-k Queries Using Views	2006	VLDB	7.8579393e-05
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