Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture

Summary: URSPRUNG integrates with execution environments to automatically capture static and runtime config, without code changes. It fuses system-level provenance with app-level signals (logs, stdout) via a DSL, achieving ~4% overhead. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12403
Venue: VLDB
Year: 2020
Pagerank: 6.5221401e-05
Overall Rank: 4,756 | 67.38%
DOI: 10.14778/3415478.3415556

Incoming Non-self Citations Over Time

Authors

1. Lukas Rupprecht (IBM)
2. James C. Davis (Virginia Tech)
3. Constantine Arnold (IBM)
4. Yaniv Gur (IBM)
5. Deepavali Bhagwat (IBM)

BibTeX Citation

@article{rupprecht_vldb20,
        title = {{Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture}},
        author = {Rupprecht, Lukas and Davis, James C. and Arnold, Constantine and Gur, Yaniv and Bhagwat, Deepavali},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {12},
        pages = {3354--3368},
        doi = {10.14778/3415478.3415556},
        url = {https://doi.org/10.14778/3415478.3415556},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,657	Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities	2021	SIGMOD	8.2887895e-05
8,576	A Study of Database Performance Sensitivity to Experiment Settings	2022	VLDB	5.4095894e-05
8,950	OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs	2023	VLDB	5.345946e-05
10,701	Unified Lineage System: Tracking Data Provenance at Scale	2025	SIGMOD	5.093636e-05
11,066	ML-Asset Management: Curation, Discovery, and Utilization	2025	VLDB	5.093636e-05
11,195	On the Feasibility and Benefits of Extensive Evaluation	2024	SIGMOD	5.093636e-05
11,650	Flow Provenance in Temporal Interaction Networks	2021	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
514	Goods: Organizing Google's Datasets	2016	SIGMOD	0.00017178673
1,475	VisTrails: Visualization meets Data Management	2006	SIGMOD	0.00010662942
1,617	Titian: Data Provenance Support in Spark	2016	VLDB	0.00010209397
1,786	Putting Lipstick on Pig: Enabling Database-style Workflow Provenance	2012	VLDB	9.7690421e-05
2,235	Decibel: The Relational Dataset Branching System	2016	VLDB	8.8913373e-05
2,431	noWorkflow: a Tool for Collecting, Analyzing, and Managing Provenance from Python Scripts	2017	VLDB	8.5875984e-05
3,614	Cloudy with High Chance of DBMS: A 10-year Prediction for Enterprise-Grade ML	2020	CIDR	7.2568185e-05
3,675	RAMP: A System for Capturing and Tracing Provenance in MapReduce Workflows	2011	VLDB	7.2096638e-05
7,878	Dependency-Driven Analytics: a Compass for Uncharted Data Oceans	2017	CIDR	5.5246167e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	2,807	Data Provenance at Internet Scale: Architecture, Experiences, and the Road Ahead	2017	CIDR
2	9,289	Compact, Tamper-Resistant Archival of Fine-Grained Provenance	2021	VLDB
3	8,950	OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs	2023	VLDB
4	919	Provenance and Scientific Workflows: Challenges and Opportunities	2008	SIGMOD
5	2,657	Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities	2021	SIGMOD
6	6,351	Tracing Lineage Beyond Relational Operators	2007	VLDB
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8	11,594	DPDS: Assisting Data Science with Data Provenance	2022	VLDB
9	11,860	Ursprung: Provenance for Large-Scale Analytics Environments	2019	SIGMOD
10	8,050	Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science	2021	VLDB