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)
Incoming Non-self Citations Over Time
Authors
- 1. Thorsten Papenbrock (Hasso-Plattner-Institut)
- 2. Tanja Bergmann (Hasso-Plattner-Institut)
- 3. Moritz Finke (Hasso-Plattner-Institut)
- 4. Jakob Zwiener (Hasso-Plattner-Institut)
- 5. Felix Naumann (Hasso-Plattner-Institut)
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.
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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 |
|---|---|---|---|---|
| 727 | Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms | 2015 | VLDB | 0.00014443394 |
| 4,226 | Scalable Discovery of Unique Column Combinations | 2014 | VLDB | 6.7183259e-05 |
| 4,246 | Divide & Conquer-based Inclusion Dependency Discovery | 2015 | VLDB | 6.7061689e-05 |
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| 1 | 9,945 | Meta-Mappings for Schema Mapping Reuse | 2019 | VLDB |
| 2 | 727 | Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms | 2015 | VLDB |
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| 5 | 13,168 | Computational Properties of Metaquerying Problems | 2000 | PODS |
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| 7 | 9,139 | MetaInsight: Automatic Discovery of Structured Knowledge for Exploratory Data Analysis | 2021 | SIGMOD |
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| 10 | 3,418 | Data Profiling – A Tutorial | 2017 | SIGMOD |