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Data Profiling with Metanome

Summary: Metanome is an extensible data profiling platform that automatically discovers metadata beyond simple statistics. It integrates state-of-the-art profiling algorithms, supports benchmarking and ranking, and provides visualization to compare approaches. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hd995f0b82055e952
Venue
VLDB
Year
2015
Pagerank
0.00010791559
Overall Rank
1,394 | 90.64%
DOI
10.14778/2824032.2824086
PDF
Download (CC BY-NC-ND 3.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{papenbrock_vldb15,
        title = {{Data Profiling with Metanome}},
        author = {Papenbrock, Thorsten and Bergmann, Tanja and Finke, Moritz and Zwiener, Jakob and Naumann, Felix},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {12},
        pages = {1860--1863},
        doi = {10.14778/2824032.2824086},
        url = {https://doi.org/10.14778/2824032.2824086},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 26 of 26 citing papers.

Rank Citing Paper Year Venue Pagerank
603 A Hybrid Approach to Functional Dependency Discovery 2016 SIGMOD 0.00015692059
1,488 Efficient Discovery of Approximate Dependencies 2018 VLDB 0.00010513265
1,537 Cardinality Estimation: An Experimental Survey 2018 VLDB 0.00010324934
1,620 Efficient Denial Constraint Discovery with Hydra 2018 VLDB 0.00010050865
1,713 SMOKE: Fine-grained Lineage at Interactive Speed 2018 VLDB 9.8129981e-05
1,972 Discovery of Approximate (and Exact) Denial Constraints 2020 VLDB 9.2829634e-05
2,748 Uni-Detect: A Unified Approach to Automated Error Detection in Tables 2019 SIGMOD 8.0572603e-05
3,419 Data Profiling – A Tutorial 2017 SIGMOD 7.3175997e-05
3,421 UGuide – User-Guided Discovery of FD-Detectable Errors 2017 SIGMOD 7.3120636e-05
4,845 Pattern Functional Dependencies for Data Cleaning 2020 VLDB 6.3808938e-05
5,112 Efficient Estimation of Inclusion Coefficient using HyperLogLog Sketches 2018 VLDB 6.2668086e-05
5,362 Can Large Language Models Predict Data Correlations from Column Names? 2023 VLDB 6.1592249e-05
5,642 DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python 2021 SIGMOD 6.0519777e-05
6,591 Mining Approximate Acyclic Schemes from Relations 2020 SIGMOD 5.7400812e-05
8,407 Crossing the finish line faster when paddling the Data Lake with KAYAK 2017 VLDB 5.3365937e-05
8,703 From Papers to Practice: The openclean Open-Source Data Cleaning Library 2021 VLDB 5.2880532e-05
8,984 DataLoom: Simplifying Data Loading with LLMs 2024 VLDB 5.2428922e-05
9,129 Discovering Similarity Inclusion Dependencies 2023 SIGMOD 5.2234298e-05
9,964 Discovering Functional Dependencies through Hitting Set Enumeration 2024 SIGMOD 5.1014161e-05
10,030 Don’t Be a Tattle-Tale: Preventing Leakages through Data Dependencies on Access Control Protected Data 2022 VLDB 5.0910473e-05
10,063 Discovering Approximate Inclusion Dependencies 2025 VLDB 5.0851868e-05
11,414 Mining Meaningful Keys and Foreign Keys with High Precision and Recall 2025 VLDB 4.9769913e-05
11,576 SplitDF: Splitting Dataframes for Memory-Efficient Data Analysis 2024 VLDB 4.9769913e-05
11,879 Statistical Schema Learning using Occam's Razor 2022 SIGMOD 4.9769913e-05
12,052 Making DBMSes Dependency-Aware 2020 CIDR 4.9769913e-05
12,220 Demonstration of Smoke: A Deep Breath of Data-Intensive Lineage Applications 2018 SIGMOD 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
728 Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms 2015 VLDB 0.00014436728
4,226 Scalable Discovery of Unique Column Combinations 2014 VLDB 6.7151469e-05
4,247 Divide & Conquer-based Inclusion Dependency Discovery 2015 VLDB 6.703008e-05
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