Unified Lineage System: Tracking Data Provenance at Scale
Summary: ULS is an end-to-end lineage aggregator tracking data flows across heterogeneous assets with a general cross-asset model. It stitches traces, enables multi-granularity navigation, and offers tunable precision/recall, scaling to billions of nodes/edges in Meta for 100+ use cases including privacy. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Gabriela Jacques-Silva (Meta)
- 2. Evangelia Kalyvianaki (Meta; University of Cambridge)
- 3. Katriel Cohn-Gordon (Meta)
- 4. Adham Meguid (Meta)
- 5. Huy Nguyen (Meta)
- 6. Danny Ben-David (Meta)
- 7. Carl Nayak (Meta)
- 8. Varun Saravagi (Meta)
- 9. George Stasa (Meta)
- 10. Ioannis Papagiannis (Meta)
- 11. David Taieb (Meta)
- 12. Kalkidan Tamirat (Meta)
- 13. Haiyang Wu (Meta)
- 14. Bo Xi (Meta)
- 15. Taining Zhang (Meta)
- 16. Qi Zhou (Meta)
BibTeX Citation
@inproceedings{jacquessilva_sigmod25,
title = {{Unified Lineage System: Tracking Data Provenance at Scale}},
author = {Jacques-Silva, Gabriela and Kalyvianaki, Evangelia and Cohn-Gordon, Katriel and Meguid, Adham and Nguyen, Huy and Ben-David, Danny and Nayak, Carl and Saravagi, Varun and Stasa, George and Papagiannis, Ioannis and Taieb, David and Tamirat, Kalkidan and Wu, Haiyang and Xi, Bo and Zhang, Taining and Zhou, Qi},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3724458},
url = {https://dl.acm.org/doi/10.1145/3722212.3724458},
year = {2025}
}
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