Υ-DB: Managing scientific hypotheses as uncertain data

Summary: Υ-DB treats deterministic scientific hypotheses as uncertain data and defines a probabilistic DB design methodology to build and manage U-relational hypothesis databases. Hypothesis management becomes a first-class p-DB application, enabling deep predictive analytics for data-driven science. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h1e3fdd56c2118289
Venue: VLDB
Year: 2014
Pagerank: 4.9793485e-05
Overall Rank: 12,509 | 15.90%
DOI: 10.14778/2732967.2732971

Incoming Non-self Citations Over Time

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Authors

1. Bernardo Gonçalves (National Laboratory for Scientific Computing)
2. Fabio Porto (National Laboratory for Scientific Computing)

BibTeX Citation

@article{goncalves_vldb14,
        title = {{Υ-DB: Managing scientific hypotheses as uncertain data}},
        author = {Gonçalves, Bernardo and Porto, Fabio},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {11},
        doi = {10.14778/2732967.2732971},
        url = {https://doi.org/10.14778/2732967.2732971},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,549	Conditioning Probabilistic Databases	2008	VLDB	0.00010288725
5,409	Data is Dead… Without What-If Models	2011	VLDB	6.1411964e-05

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