article

A survey of data provenance in e-science

Authors:

Yogesh L. Simmhan,

Dennis GannonAuthors Info & Claims

ACM SIGMOD Record, Volume 34, Issue 3

Pages 31 - 36

https://doi.org/10.1145/1084805.1084812

Published: 01 September 2005 Publication History

Abstract

Data management is growing in complexity as large-scale applications take advantage of the loosely coupled resources brought together by grid middleware and by abundant storage capacity. Metadata describing the data products used in and generated by these applications is essential to disambiguate the data and enable reuse. Data provenance, one kind of metadata, pertains to the derivation history of a data product starting from its original sources.In this paper we create a taxonomy of data provenance characteristics and apply it to current research efforts in e-science, focusing primarily on scientific workflow approaches. The main aspect of our taxonomy categorizes provenance systems based on why they record provenance, what they describe, how they represent and store provenance, and ways to disseminate it. The survey culminates with an identification of open research problems in the field.

References

[1]

J. Brase, "Using Digital Library Techniques - Registration of Scientific Primary Data," in ECDL, 2004.]]

[2]

D. G. Clarke and D. M. Clark, "Lincage," in Elements of Spatial Data Quality, 1995.]]

[3]

J. L. Romeu, "Data Quality and Pedigree," in Material Ease, 1999.]]

[4]

H. V. Jagadish and F. Olken, "Database Management for Life Sciences Research," in SIGMOD Record, vol. 33, 2004.]]

Digital Library

[5]

"Access to genetic resources and Benefit-Sharing (ABS) Program," United Nations University, 2003.]]

[6]

P. Buneman, S. Khanna, and W. C. Tan, "Why and Where: A Characterization of Data Provenance," in ICDT, 2001.]]

Digital Library

[7]

D. P. Lanter, "Design of a Lineage-Based Meta-Data Base for GIS," in Cartography and Geographic Information Systems, vol. 18, 1991.]]

[8]

M. Greenwood, C. Goble, R. Stevens, J. Zhao, M. Addis, D. Marvin, L. Moreau, and T. Oinn, "Provenance of e-Science Experiments - experience from Bioinformatics," in Proceedings of the UK OST e-Science 2nd AHM, 2003.]]

[9]

Y. L. Simmhan, B. Plale, and D. Gannon, "A Survey of Data Provenance Techniques," in Technical Report TR-618: Computer Science Department, Indiana University, 2005.]]

[10]

R. Bose and J. Frew, "Lineage retrieval for scientific data processing: a survey," in ACM Comput. Surv., vol. 37, 2005.]]

Digital Library

[11]

S. Miles, P. Groth, M. Branco, and L. Moreau, "The requirements of recording and using provenance in e-Science experiments," in Technical Report, Electronics and Computer Science, University of Southampton, 2005.]]

[12]

D. Pearson, "Presentation on Grid Data Requirements Scoping Metadata & Provenance," in Workshop on Data Derivation and Provenance, Chicago, 2002.]]

[13]

G. Cameron, "Provenance and Pragmatics," in Workshop on Data Provenance and Annotation, Edinburgh, 2003.]]

[14]

C. Goble, "Position Statement: Musings on Provenance, Workflow and (Semantic Web) Annotations for Bioinformatics," in Workshop on Data Derivation and Provenance, Chicago, 2002.]]

[15]

P. P. da Silva, D. L. McGuinness, and R. McCool, "Knowledge Provenance Infrastructure," in IEEE Data Engineering Bulletin, vol. 26, 2003.]]

[16]

H. Galhardas, D. Florescu, D. Shasha, E. Simon, and C.-A. Saita, "Improving Data Cleaning Quality Using a Data Lineage Facility," in DMDW, 2001.]]

[17]

I. T. Foster, J. S. Vöckler, M. Wilde, and Y. Zhao. "The Virtual Data Grid: A New Model and Architecture for Data-Intensive Collaboration," in CIDR, 2003.]]

[18]

J. Zhao, C. A. Goble, R. Stevens, and S. Bechhofer, "Semantically Linking and Browsing Provenance Logs for E-science," in ICSNW, 2004.]]

[19]

A. Woodruff and M. Stonebraker, "Supporting Fine-grained Data Lineage in a Database Visualization Environment," in ICDE, 1997.]]

Digital Library

[20]

B. Plale, D. Gannon, D. Reed, S. Graves, K. Droegemeier, B. Wilhelmson, and M. Ramamurthy, "Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD," in ICCS workshop on Dynamic Data Driven Applications, 2005.]]

Digital Library

[21]

D. Bhagwat, L. Chiticariu, W. C. Tan, and G. Vijayvargiya, "An Annotation Management System for Relational Databases," in VLDB, 2004.]]

[22]

Y. Cui and J. Widom, "Practical Lineage Tracing in Data Warehouses," in ICDE, 2000.]]

Digital Library

[23]

J. Widom, "Trio: A System for Integrated Management of Data, Accuracy, and Lineage," in CIDR, 2005.]]

[24]

C. Pancerella, J. Hewson, W. Koegler, D. Leahy, M. Lee, L. Rahn, C. Yang, J. D. Myers, B. Didier, R. McCoy, K. Schuchardt, E. Stephan, T. Windus, K. Amin, S. Bittner, C. Lansing, M. Minkoff, S. Nijsure, G. v. Laszewski, R. Pinzon, B. Ruscic, Al Wagner, B. Wang, W. Pitz, Y. L. Ho, D. Montoya, L. Xu, T. C. Allison, W. H. Green, Jr, and M. Frenklach, "Metadata in the collaboratory for multi-scale chemical science," in Dublin Core Conference, 2003.]]

[25]

J. Myers, C. Pancerella, C. Lansing, K. Schuchardt, and B. Didier, "Multi-Scale Science, Supporting Emerging Practice with Semantically Derived Provenance," in ISWC workshop on Semantic Web Technologies for Searching and Retrieving Scientific Data, 2003.]]

[26]

R. Bose and J. Frew, "Composing Lineage Metadata with XML for Custom Satellite-Derived Data Products," in SSDBM, 2004.]]

[27]

I. T. Foster, J.-S. Vöckler, M. Wilde, and Y. Zhao, "Chimera: A Virtual Data System for Representing, Querying, and Automating Data Derivation," in SSDBM, 2002.]]

Digital Library

[28]

J. Frew and R. Bose, "Earth System Science Workbench: A Data Management Infrastructure for Earth Science Products," in SSDBM, 2001.]]

[29]

Y. Cui and J. Widom, "Lineage tracing for general data warehouse transformations," in VLDB Journal, vol. 12, 2003.]]

Digital Library

Cited By

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A survey of data provenance in e-science

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Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 34, Issue 3

September 2005

115 pages

ISSN:0163-5808

DOI:10.1145/1084805

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Copyright © 2005 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2005

Published in SIGMOD Volume 34, Issue 3

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Cited By

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https://doi.org/10.61411/rsc202436617
Khan F(2024)Cloud‐based provenance framework for duplicates identification and data quality enhancementExpert Systems10.1111/exsy.13600Online publication date: Apr-2024
https://doi.org/10.1111/exsy.13600
In SLin TNorth CPfister HYang Y(2024)This is the Table I Want! Interactive Data Transformation on Desktop and in Virtual RealityIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.329960230:8(5635-5650)Online publication date: Aug-2024
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Burns ALee COn TXiong CPeck EMahyar N(2024)From Invisible to Visible: Impacts of Metadata in Communicative Data VisualizationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.323171630:7(3427-3443)Online publication date: Jul-2024
https://doi.org/10.1109/TVCG.2022.3231716
Han RZheng MByna STang HDong BDai DChen YKim DHassoun JThorsley D(2024)PROV-IO: A Cross-Platform Provenance Framework for Scientific Data on HPC SystemsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2024.337455535:5(844-861)Online publication date: May-2024
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Hurtado SAntequera-Gómez MBarba-González CPicornell ANavas-Delgado I(2024)e-Science workflow: A semantic approach for airborne pollen predictionKnowledge-Based Systems10.1016/j.knosys.2023.111230284(111230)Online publication date: Jan-2024
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G NHaveri PB RDeewan Y(2023)Framework for Data Provenance Assurance in Cloud Environment using Ethereum BlockchainICST Transactions on Scalable Information Systems10.4108/eetsis.3536Online publication date: 9-Oct-2023
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Ahmed MDar AHelfert MKhan AKim J(2023)Data Provenance in Healthcare: Approaches, Challenges, and Future DirectionsSensors10.3390/s2314649523:14(6495)Online publication date: 18-Jul-2023
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Sembay Mde Macedo DJúnior LBraga RSarasa-Cabezuelo A(2023)Provenance Data Management in Health Information Systems: A Systematic Literature ReviewJournal of Personalized Medicine10.3390/jpm1306099113:6(991)Online publication date: 13-Jun-2023
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