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Provenance and Annotation of Data and Processes

Overview of attention for book
Cover of 'Provenance and Annotation of Data and Processes'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 ProvAbs : Model, Policy, and Tooling for Abstracting PROV Graphs
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    Chapter 2 ProvGen: Generating Synthetic PROV Graphs with Predictable Structure
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    Chapter 3 Walking into the Future with PROV Pingback: An Application to OPeNDAP Using Prizms
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    Chapter 4 Provenance for Online Decision Making
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    Chapter 5 Regenerating and Quantifying Quality of Benchmarking Data Using Static and Dynamic Provenance
  7. Altmetric Badge
    Chapter 6 Provenance and Annotation of Data and Processes
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    Chapter 7 Label Flow: Exploiting Workflow Provenance to Surface Scientific Data Provenance
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    Chapter 8 Auditing and Maintaining Provenance in Software Packages
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    Chapter 9 An Analytical Survey of Provenance Sanitization
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    Chapter 10 A Provenance-Based Policy Control Framework for Cloud Services
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    Chapter 11 Applying Provenance to Protect Attribution in Distributed Computational Scientific Experiments
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    Chapter 12 Looking Inside the Black-Box: Capturing Data Provenance Using Dynamic Instrumentation
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    Chapter 13 Generating Scientific Documentation for Computational Experiments Using Provenance
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    Chapter 14 Computing Location-Based Lineage from Workflow Specifications to Optimize Provenance Queries
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    Chapter 15 Interrogating Capabilities of IoT Devices
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    Chapter 16 A Lightweight Provenance Pingback and Query Service for Web Publications
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    Chapter 17 Provenance-Based Searching and Ranking for Scientific Workflows
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    Chapter 18 PROV-O-Viz - Understanding the Role of Activities in Provenance
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    Chapter 19 The Aspect-Oriented Architecture of the CAPS Framework for Capturing, Analyzing and Archiving Provenance Data
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    Chapter 20 Improving Workflow Design Using Abstract Provenance Graphs
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    Chapter 21 Early Discovery of Tomato Foliage Diseases Based on Data Provenance and Pattern Recognition
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    Chapter 22 Provenance in Open Data Entity-Centric Aggregation
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    Chapter 23 Enhancing Provenance Representation with Knowledge Based on NFR Conceptual Modeling: A Softgoal Catalog Approach
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    Chapter 24 Provenance Storage, Querying, and Visualization in PBase
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    Chapter 25 Engineering Choices for Open World Provenance
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    Chapter 26 Towards Supporting Provenance Gathering and Querying in Different Database Approaches
  28. Altmetric Badge
    Chapter 27 Provenance for Explaining Taxonomy Alignments
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    Chapter 28 Challenges for Provenance Analytics Over Geospatial Data
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    Chapter 29 Adaptive RDF Query Processing Based on Provenance
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    Chapter 30 Using Well-Founded Provenance Ontologies to Query Meteorological Data
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    Chapter 31 Applying W3C PROV to Express Geospatial Provenance at Feature and Attribute Level
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    Chapter 32 ProvStore: A Public Provenance Repository
  34. Altmetric Badge
    Chapter 33 Sentence Templating for Explaining Provenance
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    Chapter 34 Extending PROV Data Model for Provenance-Aware Sensor Web
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    Chapter 35 SC-PROV: A Provenance Vocabulary for Social Computation
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    Chapter 36 RDataTracker and DDG Explorer
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    Chapter 37 Provenance Support for Medical Research
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    Chapter 38 Experiencing PROV-Wf for Provenance Interoperability in SWfMSs
  40. Altmetric Badge
    Chapter 39 Erratum to: Provenance in Open Data Entity-Centric Aggregation
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

blogs
2 blogs
twitter
1 X user
patent
1 patent
video
1 YouTube creator

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
13 Mendeley
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Title
Provenance and Annotation of Data and Processes
Published by
Lecture notes in computer science, March 2015
DOI 10.1007/978-3-319-16462-5
ISBNs
978-3-31-916461-8, 978-3-31-916462-5
Authors

Cheney, James, Perera, Roly

Editors

Bertram Ludäscher, Beth Plale

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 15%
Student > Ph. D. Student 2 15%
Other 1 8%
Librarian 1 8%
Lecturer 1 8%
Other 0 0%
Unknown 6 46%
Readers by discipline Count As %
Computer Science 3 23%
Agricultural and Biological Sciences 1 8%
Earth and Planetary Sciences 1 8%
Social Sciences 1 8%
Unknown 7 54%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 October 2023.
All research outputs
#2,111,690
of 26,017,215 outputs
Outputs from Lecture notes in computer science
#342
of 8,229 outputs
Outputs of similar age
#26,450
of 281,488 outputs
Outputs of similar age from Lecture notes in computer science
#4
of 93 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,229 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 281,488 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.