SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics

Summary: SeeDB is a data-driven visualization recommender that, for a data subset, quickly explores visualizations to surface relevant trends. It uses pruning and sharing for interactive latency, adopts a deviation-based utility metric, and runs as DBMS middleware to deliver orders-of-magnitude speedups for visual analytics. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11322
Venue: VLDB
Year: 2015
Pagerank: 0.0001890421
Overall Rank: 410 | 97.19%
DOI: 10.14778/2831360.2831371

Incoming Non-self Citations Over Time

Authors

1. Manasi Vartak (Massachusetts Institute of Technology)
2. Sajjadur Rahman (University of Illinois Urbana-Champaign)
3. Samuel Madden (Massachusetts Institute of Technology)
4. Aditya Parameswaran (University of Illinois Urbana-Champaign)
5. Neoklis Polyzotis (Google)

BibTeX Citation

@article{vartak_vldb15,
        title = {{SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics}},
        author = {Vartak, Manasi and Rahman, Sajjadur and Madden, Samuel and Parameswaran, Aditya and Polyzotis, Neoklis},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {13},
        pages = {2182--2193},
        doi = {10.14778/2831360.2831371},
        url = {https://doi.org/10.14778/2831360.2831371},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 51 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
12,000	A Declarative Query Processing System for Nowcasting	2017	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
11	Implementing Data Cubes Efficiently	1996	SIGMOD	0.00071822821
191	Scorpion: Explaining Away Outliers in Aggregate Queries	2013	VLDB	0.00026096009
207	On the Computation of Multidimensional Aggregates	1996	VLDB	0.00025088003
509	Supporting Top-k Join Queries in Relational Databases	2003	VLDB	0.00017220967
700	Explaining differences in multidimensional aggregates	1999	VLDB	0.00014871032
915	Intelligent Rollups in Multidimensional OLAP Data	2001	VLDB	0.00013243386
965	User-adaptive exploration of multidimensional data	2000	VLDB	0.00012933878
1,098	Google Fusion Tables: Web-Centered Data Management and Collaboration	2010	SIGMOD	0.00012179025
1,634	Rapid Sampling for Visualizations with Ordering Guarantees	2015	VLDB	0.00010163938
1,932	VizDeck: Self-Organizing Dashboards for Visual Analytics	2012	SIGMOD	9.4646634e-05
1,933	Red Brick Warehouse: A Read-Mostly RDBMS for Open SMP Platforms	1994	SIGMOD	9.4642118e-05
3,350	Support the Data Enthusiast: Challenges for Next-Generation Data-Analysis Systems	2014	VLDB	7.4942163e-05
4,864	SeeDB: Automatically Generating Query Visualizations	2014	VLDB	6.4736789e-05
5,329	SeeDB: Visualizing Database Queries Efficiently	2014	VLDB	6.2634965e-05

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1	8,174	Databases will Visualize Queries too	2011	VLDB
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3	5,177	Databases and Visualization	1996	SIGMOD
4	3,425	Foresight: Recommending Visual Insights	2017	VLDB
5	13,565	Data Visualization Management Systems	2015	CIDR
6	14,276	VisDB: A System for Visualizing Large Databases	1995	SIGMOD
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9	4,864	SeeDB: Automatically Generating Query Visualizations	2014	VLDB
10	5,329	SeeDB: Visualizing Database Queries Efficiently	2014	VLDB