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Boris Glavic, Marta Mattoso (Beteiligte)

Provenance and Annotation of Data and Processes


6th International Provenance and Annotation Workshop, IPAW 2016, McLean, VA, USA, June 7-8, 2016, Proceedings
Herausgegeben von Mattoso, Marta; Glavic, Boris
1st ed. 2016. 2016. xi, 236 S. 80 SW-Abb. 235 mm
Verlag/Jahr: SPRINGER, BERLIN; SPRINGER INTERNATIONAL PUBLISHING 2016
ISBN: 3-319-40592-6 (3319405926)
Neue ISBN: 978-3-319-40592-6 (9783319405926)

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This book constitutes the refereed proceedings of the 6th International Provenance and Annotation Workshop, IPAW 2016, held in McLean, VA, USA, in June 2016.
The 12 revised full papers, 14 poster papers, and 2 demonstration papers presented were carefully reviewed and selected from 54 submissions. The papers feature state-of-the-art research and practice around the automatic capture, representation, and use of provenance. They are organized in topical sections on provenance capture, provenance analysis and visualization, and provenance models and applications.
RecProv: Towards Provenance-Aware Userspace Record and Replay.- Tracking and Analyzing the Evolution of Provenance from Scripts.- Trade-offs in Automatic Provenance Capture.- Analysis of Memory Constrained Live Provenance.- Analyzing Provenance across Heterogeneous Provenance Graphs.- Prov Viewer: A Graph-Based Visualization Tool for Interactive Exploration of Provenance Data.- Intermediate Notation for Provenance and Workflow Reproducibility.- Towards the Domain Agnostic Generation of Natural Language Explanations from Provenance Graphs for Casual Users.- Versioning Version Trees: The Provenance of Actions that Affect Multiple Versions.- Enabling Web Service Request Citation by Provenance Information.- Modelling Provenance of Sensor Data for Food Safety Compliance Checking.- Modelling Provenance Collection Points and Their Impact on Provenance Graphs.- Yin & Yang: Demonstrating Complementary Provenance from NoWorkflow & YesWorkflow.- MPO: a System to Document and Analyze Distributed Heterogeneous Workflows.- PROV-JSONLD: A JSON and Linked Data Representation for Provenance.- Provenance as Essential Infrastructure for Data Lakes.- Provenance-Based Retrieval: Fostering Reuse and Reproducibility across Scientific Disciplines.- Addressing Scientific Rigor in Data Analytics Using Semantic Workflows.- Reconstructing Human-Generated Provenance through Similarity-Based Clustering.- Social Media Data in Research: Provenance Challenges.- Fine-Grained Provenance Collection over Scripts Through Program Slicing.- Prov2ONE: An Algorithm for Automatically Constructing ProvONE Provenance Graphs.- Implementing Unied Why- and Why-Not Provenance through Games.- SisGExp: Rethinking Long-Tail Agronomic Experiments.- Towards Provenance Capturing of Quantified Self Data.- A Review of Guidelines and Models for Representation of Provenance Information from Neuroscience Experiments.- Tracking and Establishing Provenance of Earth Science Datasets: A NASA-Based Example.- DataONE: A Data Federation with Provenance Support.