Provenance data science models (15 résultats)
Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-UnisGreatBookPrices
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 134,92
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Etat : New.
Langue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
Vendeur : Ria Christie Collections, Uxbridge, Royaume-UniRia Christie Collections
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 139,13
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Etat : New. In.
Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-UniGreatBookPricesUK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 136,67
EUR 17,48 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New.
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : Ria Christie Collections, Uxbridge, Royaume-UniRia Christie Collections
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 140,88
EUR 13,96 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New. In.
Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-UnisGreatBookPrices
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion - Comme neuf
EUR 154,18
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Etat : As New. Unread book in perfect condition.
Provenance in Data Science : From Data Models to Context-aware Knowledge Graphs
Sikos, Leslie F. (EDT); Seneviratne, Oshani W. (EDT); McGuinness, Deborah L. (EDT)
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-UniGreatBookPricesUK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion - Comme neuf
EUR 156,17
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Etat : As New. Unread book in perfect condition.
Langue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
Vendeur : Books Puddle, New York, NY, Etats-UnisBooks Puddle
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 208,62
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Etat : New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Autres imagesLangue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
Vendeur : preigu, Osnabrück, Allemagnepreigu
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 140,10
EUR 70,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 5 disponible(s)
Taschenbuch. Etat : Neu. Provenance in Data Science | From Data Models to Context-Aware Knowledge Graphs | Leslie F. Sikos (u. a.) | Taschenbuch | Advanced Information and Knowledge Processing | xi | Englisch | 2022 | Springer | EAN 9783030676834 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121… Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Langue : anglais
Edité par Palgrave Macmillan, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : Buchpark, Trebbin, AllemagneBuchpark
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion
EUR 118,72
EUR 105,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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, knowled…ge 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, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 162,91
EUR 61,80 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Langue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
Vendeur : Buchpark, Trebbin, AllemagneBuchpark
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion
EUR 122,67
EUR 105,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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, knowled…ge 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, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Langue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 167,14
EUR 61,01 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack mapsthat aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues.This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Provenance in Data Science: From Data Models to Context-Aware Knowledge Graphs
Sikos, Leslie F. (Edited by)/ Seneviratne, Oshani W. (Edited by)/ McGuinness, Deborah L. (Edited by)
Langue : anglais
Edité par Springer, 2021
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture rigide
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 233,63
EUR 11,65 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Hardcover. Etat : Brand New. 121 pages. 9.25x6.10x0.51 inches. In Stock.
Langue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
- impression à la demande
Vendeur : Majestic Books, Hounslow, Royaume-UniMajestic Books
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 219,11
EUR 7,58 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 4 disponible(s)
Etat : New. Print on Demand.
Langue : anglais
Edité par Springer, 2022
Série : Livre 65 sur 66 - Advanced Information and Knowledge Processing
- Couverture souple
- impression à la demande
Vendeur : Biblios, frankfurt am main, HESSE, AllemagneBiblios
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 224,47
EUR 9,95 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 4 disponible(s)
Etat : New. PRINT ON DEMAND.
