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 |
|---|---|---|---|---|
| 729 | Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms | 2015 | VLDB | 0.00014539421 |
| 4,183 | Scalable Discovery of Unique Column Combinations | 2014 | VLDB | 6.8467773e-05 |
| 4,386 | Divide & Conquer-based Inclusion Dependency Discovery | 2015 | VLDB | 6.7309577e-05 |
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| 1 | 9,790 | Meta-Mappings for Schema Mapping Reuse | 2019 | VLDB |
| 2 | 729 | Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms | 2015 | VLDB |
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| 4 | 1,356 | Metadata Management for Large Statistical Databases | 1982 | VLDB |
| 5 | 12,878 | Computational Properties of Metaquerying Problems | 2000 | PODS |
| 6 | 11,743 | Making DBMSes Dependency-Aware | 2020 | CIDR |
| 7 | 8,974 | MetaInsight: Automatic Discovery of Structured Knowledge for Exploratory Data Analysis | 2021 | SIGMOD |
| 8 | 7,038 | Towards NLP-Enhanced Data Profiling Tools | 2022 | CIDR |
| 9 | 11,542 | Simplifying Access to Large-scale Structured Datasets by Meta-Profiling with Scalable Training Set Enrichment | 2022 | SIGMOD |
| 10 | 3,387 | Data Profiling – A Tutorial | 2017 | SIGMOD |