The Full Provenance Stack: Five Layers for Complete and Meaningful Provenance
Integrity signals
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W3C PROV is capable of capturing aspects relevant for compliance and accountability, for example recording which parties undertook various activities with regard to data, or modelling GDPR compliance.
“W3C PROV is capable of capturing aspects relevant for compliance and accountability, for example, for recording which parties undertook various activities with regard to data, or modelling GDPR compliance [49].”
From Decision Provenance: Harnessing Data Flow for Accountable Systems (2019) · cites this paper as [49]
Cites
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Chimera: a virtual data system for representing, querying, and automating data derivation
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Provenance-Aware Storage Systems
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Examining the Challenges of Scientific Workflows
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Conditional functional dependencies for capturing data inconsistencies
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TrustCloud: A Framework for Accountability and Trust in Cloud Computing
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Self-citationProvenance management in curated databases
Buneman, P., Chapman, A. P., & Cheney, J. (2006) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/1142473.1142534 · Cited by 298 · see citing works
Using Semantic Web Technologies for Representing E-science Provenance
Zhao, J., Wroe, C., Goble, C., Stevens, R., Quan, D., & Greenwood, R. M. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30475-3_8 · Cited by 151 · see citing works
Layering in provenance systems
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On the expressiveness of implicit provenance in query and update languages
Buneman, P., Cheney, J., & Vansummeren, S. (2008) · ACM Transactions on Database Systems · doi:10.1145/1412331.1412340 · Cited by 108 · see citing works
Ko, R. K. L., Jagadpramana, P., & Lee, B. (2011) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom.2011.100 · Cited by 82 · see citing works
Self-citationProgger: An Efficient, Tamper-Evident Kernel-Space Logger for Cloud Data Provenance Tracking
Ko, R. K. L., & Will, M. A. (2014) · IEEE ... International Conference on Cloud Computing · doi:10.1109/cloud.2014.121 · Cited by 74 · see citing works
Self-citationS2Logger: End-to-End Data Tracking Mechanism for Cloud Data Provenance
Suen, C. H., Ko, R. K. L., Tan, Y. S., Jagadpramana, P., & Lee, B. (2013) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom.2013.73 · Cited by 72 · see citing works
Self-citationProvenance: an alternate history of art
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How to Track Your Data: The Case for Cloud Computing Provenance
Zhang, O. Q., Kirchberg, M., Ko, R. K. L., & Lee, B. (2011) · IEEE International Conference on Cloud Computing Technology and Science · doi:10.1109/cloudcom.2011.66 · Cited by 57 · see citing works
Self-citationGetty Research Institute, Los Angeles
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Composing and conveying lineage metadata for environmental science research computing
Bose, R., & Frew, J. E. (2004) · Cited by 4 · see citing works
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Decision Provenance: Harnessing Data Flow for Accountable Systems
Singh, J., Cobbe, J., & Norval, C. (2019) · IEEE Access · doi:10.1109/access.2018.2887201 · Cited by 110 · see citing works
- Authors
- Ko, R. K. L., & Phua, T. W.
- Affiliations
- University of Waikato (NZ)
- Corresponding author
- Ko, Ryan K. L.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2017
- Pages
- 180-193
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2771930793
- Cited by
- 5
- References
- 18
- Citations by year
- 2022: 1 · 2021: 1 · 2019: 1 · 2018: 2
- FWCI
- 0.63
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Digital and Cyber Forensics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Keywords
- data provenance, cybersecurity, digital forensics, data privacy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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