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An Algebraic Approach for Data-Centric Scientific Workflows

Summary: Algebraic approach inspired by relational algebra, plus a parallel execution model to automatically optimize data-centric scientific workflows. Validated on oil-exploitation and synthetic data with the Chiron engine, achieving up to 226% speedup vs ad-hoc implementations. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hd5c47418c4197cbf
Venue
VLDB
Year
2011
Pagerank
5.6225586e-05
Overall Rank
7,008 | 52.89%
DOI
10.14778/3402755.3402766

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{ogasawara_vldb11,
        title = {{An Algebraic Approach for Data-Centric Scientific Workflows}},
        author = {Ogasawara, Eduardo and Dias, Jonas and de Oliveira, Daniel and Porto, Fábio and Valduriez, Patrick and Mattoso, Marta},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {12},
        pages = {1328--1339},
        doi = {10.14778/3402755.3402766},
        url = {https://doi.org/10.14778/3402755.3402766},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
2,550 SQLShare: Results from a Multi-Year SQL-as-a-Service Experiment 2016 SIGMOD 8.3121033e-05
8,376 Meta-Dataflows: Efficient Exploratory Dataflow Jobs 2018 SIGMOD 5.3437059e-05
9,969 DfAnalyzer: Runtime Dataflow Analysis of Scientific Applications using Provenance 2018 VLDB 5.1038322e-05
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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.

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