Provenance and Annotation of Data and Processes

1. Front Matter

   Pages I-X

   PDF

2. Reproducibility

   1. Front Matter

      Pages 1-1

      PDF

   2. Provenance Annotation and Analysis to Support Process Re-computation

      • Jacek Cała, Paolo Missier

      Pages 3-15

   3. Provenance of Dynamic Adaptations in User-Steered Dataflows

      • Renan Souza, Marta Mattoso

      Pages 16-29

   4. Classification of Provenance Triples for Scientific Reproducibility: A Comparative Evaluation of Deep Learning Models in the ProvCaRe Project

      • Joshua Valdez, Matthew Kim, Michael Rueschman, Susan Redline, Satya S. Sahoo

      Pages 30-41

3. Modeling, Simulating and Capturing Provenance

   1. Front Matter

      Pages 43-43

      PDF

   2. A Provenance Model for the European Union General Data Protection Regulation

      • Benjamin E. Ujcich, Adam Bates, William H. Sanders

      Pages 45-57

   3. Automating Provenance Capture in Software Engineering with UML2PROV

      • Carlos Sáenz-Adán, Luc Moreau, Beatriz Pérez, Simon Miles, Francisco J. García-Izquierdo

      Pages 58-70

   4. Simulated Domain-Specific Provenance

      • Pinar Alper, Elliot Fairweather, Vasa Curcin

      Pages 71-83

4. PROV Extensions

   1. Front Matter

      Pages 85-85

      PDF

   2. Versioned-PROV: A PROV Extension to Support Mutable Data Entities

      • João Felipe N. Pimentel, Paolo Missier, Leonardo Murta, Vanessa Braganholo

      Pages 87-100

   3. Using the Provenance from Astronomical Workflows to Increase Processing Efficiency

      • Michael A. C. Johnson, Luc Moreau, Adriane Chapman, Poshak Gandhi, Carlos Sáenz-Adán

      Pages 101-112

5. Scientific Workflows

   1. Front Matter

      Pages 113-113

      PDF

   2. Discovering Similar Workflows via Provenance Clustering: A Case Study

      • Abdussalam Alawini, Leshang Chen, Susan Davidson, Stephen Fisher, Junhyong Kim

      Pages 115-127

   3. Validation and Inference of Schema-Level Workflow Data-Dependency Annotations

      • Shawn Bowers, Timothy McPhillips, Bertram Ludäscher

      Pages 128-141

6. Applications

   1. Front Matter

      Pages 143-143

      PDF

   2. Belief Propagation Through Provenance Graphs

      • Belfrit Victor Batlajery, Mark Weal, Adriane Chapman, Luc Moreau

      Pages 145-157

   3. Using Provenance to Efficiently Propagate SPARQL Updates on RDF Source Graphs

      • Iman Naja, Nicholas Gibbins

      Pages 158-170

7. System Demonstrations

   1. Front Matter

      Pages 171-171

      PDF

   2. Implementing Data Provenance in Health Data Analytics Software

      • Shen Xu, Elliot Fairweather, Toby Rogers, Vasa Curcin

      Pages 173-176

This book constitutes the refereed proceedings of the 7th International Provenance and Annotation Workshop, IPAW 2018, held in London, UK, in July 2018.
The 12 revised full papers, 19 poster papers, and 2 demonstration papers presented were carefully reviewed and selected from 50 submissions. The papers feature a variety of provenance-related topics ranging from the capture and inference of provenance to its use and application.They are organized in topical sections on reproducibility; modeling, simulating and capturing provenance; PROV extensions; scientific workflows; applications; and system demonstrations.

• artificial intelligence
• big data
• cloud computing
• computer systems
• data privacy
• data security
• databases
• debugging
• internet
• map-reduce
• metadata
• ontologies
• program debugging
• programming languages
• semantic web
• semantics
• software engineering
• user interfaces
• world wide web

• Paris Dauphine University, Paris, France

  Khalid Belhajjame

• SRI International, Menlo Park, USA

  Ashish Gehani

• University of Luxembourg, Belvaux, Luxembourg

  Pinar Alper

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