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Efficient Lineage Tracking For Scientific Workflows

Summary: Introduces an interval-based, space- and query-efficient representation for data lineage graphs from scientific workflows, avoiding recursive storage. Transforms any workflow processes into compact dependency graphs and offers analysis plus evaluation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4111
Venue
SIGMOD
Year
2008
Pagerank
9.5783449e-05
Overall Rank
1,871 | 87.17%
DOI
10.1145/1376616.1376716

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{heinis_sigmod08,
        title = {{Efficient Lineage Tracking For Scientific Workflows}},
        author = {Heinis, Thomas and Alonso, Gustavo},
        series = {{SIGMOD} '08},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1376616.1376716},
        url = {https://dl.acm.org/doi/10.1145/1376616.1376716},
        year = {2008}
}

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