A survey of data provenance in e-science

By Yogesh L. Simmhan, Beth Plale, Dennis Gannon. SGMD, 2005

1,364 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/2809d4876e34b8c64fc1783fe6a0a278770505b0

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In Computer Networks and Communications

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Citations in the corpus

Provenance in Databases: Why, How, and Where (2009, background): “Although there is some overlap with database and data provenance research, we will restrict attention to work that focuses on provenance within databases, and refer readers interested in workflow provenance to recent surveys [8, 53] and a recent tutorial [29].”
Spark: Cluster Computing with Working Sets (2010, background): “We refer the reader to [7], [23] and [9] for surveys of this work.”
ProvDB: A System for Lifecycle Management of Collaborative Analysis Workflows (2016, background): “In scientiﬁc workﬂow systems [1,2,12,13,13,14,29,33,35,36,54] where the operations are typically treated as black boxes, the provenance can usually be captured only at the level of datasets.”
Efficient, Distributed and Interactive Neuroimaging Data Analysis Using the LONI Pipeline (2009, positive): “Provenance can be used for determining data quality, for result interpretation, and for protocol interoperability (Simmhan et al., 2005; Zhao et al., 2007).”
Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber-physical convergence (2012, neutral): “• Reproducibility As both the scale and complexity of datasets are increasing, it is critical to be able to reproduce a computational procedure and its result [71,72].”
A survey of trust in computer science and the Semantic Web (2007, background): “[105] and Moreau and udaescher [106] provide overviews of provenance research in cientific applications.”
Provenance Collection Support in the Kepler Scientific Workflow System (2006, neutral): “[6].”
Managing Rapidly-Evolving Scientific Workflows (2006, background): “, maintaining information of how a given data product is generated [6,7,11].”
A survey on provenance: What for? What form? What from? (2017, background): “Therefore, and further being inspired by previous classifications of provenance applications and applications [83,87,162,166], our discussion is structured around particular applications.”
Big data challenge: a data management perspective (2013, background): “In addition to the original data, provenance data (recording how data are generated and transformed) are very important for scientific data management [4].”
ProvChain: A Blockchain-Based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability (2017, background): “Provenance is a process that determines the history of a data product, starting from its original sources [1].”
Provenance management in curated databases (2006, background): “As mentioned in the introduction, “workﬂow” or “coarse-grained” provenance has been studied extensively in the context of scien-tiﬁc computation [10, 14, 26]; Bose and Frew [3] and Simmhan et al. [21] survey most existing research on such systems.”
Cloud Computing and Grid Computing 360-Degree Compared (2008, background): “On the other hand, Clouds are becoming the future playground for e-science research, and provenance management is extremely important in order to track the processes and support the reproducibility of scientific results [45].”
Participatory provenance as representational auditing for AI-mediated public consultation (2026, unknown): “…the origin, transformation and lineage of data through processing pipelines, is well-established in database systems [Bune-man et al., 2001, Simmhan et al., 2005, Herschel et al., 2017], but has not been adapted to the specific challenge of tracking how individual citizen voices are…”