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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
hcc32e1f189d2c148
Venue
VLDB
Year
2015
Pagerank
0.00019125046
Overall Rank
395 | 97.36%
DOI
10.14778/2831360.2831371
PDF
Download (CC BY-NC-ND 3.0)

Incoming Non-self Citations Over Time

Authors

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 50 of 53 citing papers.

Rank Citing Paper Year Venue Pagerank
924 Effortless Data Exploration with zenvisage: An Expressive and Interactive Visual Analytics System 2017 VLDB 0.00013033863
1,151 Data Management Challenges in Production Machine Learning 2017 SIGMOD 0.000117662
1,306 Detecting Data Errors: Where are we and what needs to be done? 2016 VLDB 0.00011076619
2,040 Database Learning: Toward a Database that Becomes Smarter Every Time 2017 SIGMOD 9.1319608e-05
2,057 Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning 2020 SIGMOD 9.0995439e-05
2,675 Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries 2018 VLDB 8.1273838e-05
2,848 Towards Sustainable Insights or why polygamy is bad for you 2017 CIDR 7.9234942e-05
3,110 Lux: Always-on Visualization Recommendations for Exploratory Dataframe Workflows 2022 VLDB 7.6228505e-05
3,200 Extracting Top-K Insights from Multi-dimensional Data 2017 SIGMOD 7.5250098e-05
3,348 I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making 2017 VLDB 7.3783668e-05
3,971 Smile: A System to Support Machine Learning on EEG Data at Scale 2019 VLDB 6.8764774e-05
4,345 Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks 2021 SIGMOD 6.6388774e-05
4,519 Automating Exploratory Data Analysis via Machine Learning: An Overview 2020 SIGMOD 6.551459e-05
4,747 QuickInsights: Quick and Automatic Discovery of Insights from Multi-Dimensional Data 2019 SIGMOD 6.4260676e-05
5,049 Adaptive Sampling for Rapidly Matching Histograms 2018 VLDB 6.287033e-05
5,094 Data Collection and Quality Challenges for Deep Learning 2020 VLDB 6.264232e-05
5,355 Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First 2026 CIDR 6.1514948e-05
5,546 Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data 2020 SIGMOD 6.071729e-05
5,655 DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python 2021 SIGMOD 6.0320824e-05
5,773 DeepEye: Creating Good Data Visualizations by Keyword Search 2018 SIGMOD 5.981599e-05
6,530 Fast-Forwarding to Desired Visualizations with zenvisage 2017 CIDR 5.7368132e-05
6,772 Spade: A Modular Framework for Analytical Exploration of RDF Graphs 2019 VLDB 5.669182e-05
6,895 Towards Democratizing Relational Data Visualization 2019 SIGMOD 5.6382396e-05
6,955 REACT: Context-Sensitive Recommendations for Data Analysis 2016 SIGMOD 5.6193552e-05
7,131 COVIZ: A System for Visual Formation and Exploration of Patient Cohorts 2019 VLDB 5.580601e-05
7,720 Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams 2022 VLDB 5.4542911e-05
8,229 Falcon: Fair Active Learning using Multi-armed Bandits 2024 VLDB 5.3578737e-05
8,375 FEDEX: An Explainability Framework for Data Exploration Steps 2022 VLDB 5.3280107e-05
8,727 Modern Recommender Systems: from Computing Matrices to Thinking with Neurons 2018 SIGMOD 5.2705676e-05
9,044 LensXPlain: Visualizing and Explaining Contributing Subsets for Aggregate Query Answers 2019 VLDB 5.2176863e-05
9,224 Data-Driven Insight Synthesis for Multi-Dimensional Data 2024 VLDB 5.1913816e-05
9,555 Efficient Exploration of Interesting Aggregates in RDF Graphs 2021 SIGMOD 5.1487688e-05
9,612 On Detecting Cherry-picked Generalizations 2022 VLDB 5.1376962e-05
9,990 Fair and Actionable Causal Prescription Ruleset 2025 SIGMOD 5.0845476e-05
10,209 Towards Autonomous, Hands-Free Data Exploration 2020 CIDR 5.0491152e-05
10,225 COMPARE: Accelerating Groupwise Comparison in Relational Databases for Data Analytics 2021 VLDB 5.0460607e-05
10,547 Interpretable Attribute Discretization 2026 SIGMOD 4.9605343e-05
10,697 Causal Explanations for Disparate Trends: Where and Why? 2026 SIGMOD 4.9605343e-05
10,702 Data-Semantics-Aware Recommendation of Diverse Pivot Tables 2026 SIGMOD 4.9605343e-05
10,925 PipeLens: Identifying Interventions for Resolving Malfunctioning Data Science Pipelines 2026 VLDB 4.9605343e-05
11,029 DataMagic: Transforming Tabular Data into Data Insight Video 2026 VLDB 4.9605343e-05
11,231 SeerCuts: Explainable Attribute Discretization 2025 SIGMOD 4.9605343e-05
11,385 LakeVisage: Towards Scalable, Flexible and Interactive Visualization Recommendation for Data Discovery over Data Lakes 2025 VLDB 4.9605343e-05
11,422 Finding Convincing Views to Endorse a Claim 2025 VLDB 4.9605343e-05
11,438 Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models 2025 VLDB 4.9605343e-05
11,508 SDEcho: Efficient Explanation of Aggregated Sequence Difference 2025 VLDB 4.9605343e-05
11,782 Efficient Approximation Framework for Attribute Recommendation 2023 SIGMOD 4.9605343e-05
12,029 Exploring Ratings in Subjective Databases 2021 SIGMOD 4.9605343e-05
12,118 Interactive View Recommendation 2020 SIGMOD 4.9605343e-05
12,235 Enabling Data Science for the Majority 2019 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

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