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Mosaic: A Sample-Based Database System for Open World Query Processing

Summary: Mosaic: a sample-centric DBMS and SQL extensions that treats arbitrarily biased, unknown-probability samples as first-class citizens to enable open-world population queries. Introduces a sample-based data model and novel debiasing/query-answering techniques with preliminary evaluation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
361
Venue
CIDR
Year
2020
Pagerank
5.9361728e-05
Overall Rank
6,262 | 57.04%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{orr_cidr20,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '20},
        title = {{Mosaic: A Sample-Based Database System for Open World Query Processing}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Orr, Laurel and Ainsworth, Samuel and Cai, Walter and Jamieson, Kevin and Balazinska, Magda and Suciu, Dan},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
7,838 Consistent Range Approximation for Fair Predictive Modeling 2023 VLDB 5.5343411e-05
10,339 Aegis: A Correlation-Based Data Masking Advisor for Data-Sharing Ecosystems 2026 SIGMOD 5.093636e-05
10,831 Holistic query Approximation via RL Modeling 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

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

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