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Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs

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Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs - Sikos, Leslie F. (Editor), and Seneviratne, Oshani W. (Editor), and McGuinness, Deborah L. (Editor)
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RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, ...

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Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs 2022, Springer Nature Switzerland AG, Cham

ISBN-13: 9783030676834

Paperback

Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs 2021, Springer Nature Switzerland AG, Cham

ISBN-13: 9783030676803

Hardcover