Tracking Personal Data Use: Provenance And Trust
Summary: Advocate Personal Data Use Workbenches to let individuals trace how organizations process and combine their personal data. Pose DB challenges: trust/disclosure tradeoffs, operator heterogeneity needing provenance APIs/high-level specs, and new forward/backward and graph-pattern provenance queries requiring efficient execution. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lucja Kot
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,798 | Privacy-Preserving Network Provenance | 2017 | VLDB | 4.1945683e-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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 923 | Provenance and Scientific Workflows: Challenges and Opportunities | 2008 | SIGMOD | 0.0001527609 |
| 1,440 | Provenance for Generalized Map and Reduce Workflows | 2011 | CIDR | 0.00011961469 |
| 2,028 | Putting Lipstick on Pig: Enabling Database-style Workflow Provenance | 2012 | VLDB | 9.7433981e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,945 | A Demonstration of TripleProv: Tracking and Querying Provenance over Web Data | 2015 | VLDB | 4.1945683e-05 |
| 9,130 | Enabling Personal Consent in Databases | 2022 | VLDB | 4.3900952e-05 |
| 6,515 | Provenance Views for Module Privacy | 2011 | PODS | 5.0321577e-05 |
| 7,417 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 4.7355114e-05 |
| 923 | Provenance and Scientific Workflows: Challenges and Opportunities | 2008 | SIGMOD | 0.0001527609 |
| 2,173 | Querying Data Provenance | 2010 | SIGMOD | 9.3676609e-05 |
| 2,892 | Data Provenance at Internet Scale: Architecture, Experiences, and the Road Ahead | 2017 | CIDR | 7.9480559e-05 |
| 8,163 | Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science | 2021 | VLDB | 4.5723431e-05 |
| 11,471 | On Optimizing the Trade-off between Privacy and Utility in Data Provenance | 2021 | SIGMOD | 4.1945683e-05 |
| 7,132 | Enabling Privacy in Provenance-Aware Workflow Systems | 2011 | CIDR | 4.8227603e-05 |