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  • 1
    UID:
    edoccha_BV048214744
    Format: 1 Online-Ressource (XXIV, 544 Seiten) : , Illustrationen.
    ISBN: 978-3-030-78307-5
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-3-030-78306-8
    Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-78309-9
    Language: English
    Keywords: Data Mining ; Big Data ; Expertensystem ; Aufsatzsammlung
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Author information: Zillner, Sonja
    Author information: Metzger, Andreas 1973-
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    edocfu_BV048214744
    Format: 1 Online-Ressource (XXIV, 544 Seiten) : , Illustrationen.
    ISBN: 978-3-030-78307-5
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-3-030-78306-8
    Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-78309-9
    Language: English
    Keywords: Data Mining ; Big Data ; Expertensystem ; Aufsatzsammlung
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Author information: Zillner, Sonja
    Author information: Metzger, Andreas 1973-
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    b3kat_BV048214744
    Format: 1 Online-Ressource (XXIV, 544 Seiten) , Illustrationen
    ISBN: 9783030783075
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-3-030-78306-8
    Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-3-030-78309-9
    Language: English
    Keywords: Data Mining ; Big Data ; Expertensystem ; Aufsatzsammlung
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Author information: Zillner, Sonja
    Author information: Metzger, Andreas 1973-
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    b3kat_BV047463863
    Format: 1 Online-Ressource
    ISBN: 9783030710699
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-71068-2
    Language: English
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
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  • 5
    UID:
    almafu_9959968318002883
    Format: 1 online resource (416 p.)
    ISBN: 3-030-71069-6
    Content: This edited open access book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources. As a European initiative, the goal is to use these new findings to support decision-makers and producers – meaning farmers, land and forest owners and fishermen. With their 27 pilot projects from 17 countries, the authors examine important sectors and highlight examples where modern data-driven methods were used to increase sustainability. How can farmers, foresters or fishermen use these insights in their daily lives? The authors answer this and other questions for our readers. The first four parts of this book give an overview of the big data technologies relevant for optimal raw material gathering. The next three parts put these technologies into perspective, by showing useable applications from farming, forestry and fishery. The final part of this book gives a summary and a view on the future. With its broad outlook and variety of topics, this book is an enrichment for students and scientists in bioeconomy, biodiversity and renewable resources.
    Note: Description based upon print version of record. , Intro -- Foreword -- Introduction -- Glossary -- Contents -- Part I Technological Foundation: Big Data Technologies for BioIndustries -- 1 Big Data Technologies in DataBio -- 1.1 Basic Concepts of Big Data -- 1.2 Pipelines and the BDV Reference Model -- 1.3 Open, Closed and FAIR Data -- 1.4 The DataBio Platform -- 1.5 Introduction to the Technology Chapters -- Literature -- 2 Standards and EO Data Platforms -- 2.1 Introduction -- 2.2 Standardization Organizations and Initiatives -- 2.2.1 The Role of Location in Bioeconomy -- 2.2.2 The Role of Semantics in Bioeconomy , 2.3 Architecture Building Blocks for Cloud Based Services -- 2.4 Principles of an Earth Observation Cloud Architecture for Bioeconomy -- 2.4.1 Paradigm Shift: From SOA to Web API -- 2.4.2 Data and Processing Platform -- 2.4.3 Exploitation Platform -- 2.5 Standards for an Earth Observation Cloud Architecture -- 2.5.1 Applications and Application Packages -- 2.5.2 Application Deployment and Execution Service (ADES) -- 2.5.3 Execution Management Service (EMS) -- 2.5.4 AP, ADES, and EMS Interaction -- 2.6 Standards for Billing and Quoting -- 2.7 Standards for Security , 2.8 Standards for Discovery, Cataloging, and Metadata -- 2.9 Summary -- References -- Part II Data Types -- 3 Sensor Data -- 3.1 Introduction -- 3.2 Internet of Things in Bioeconomy Sectors -- 3.3 Examples from DataBio -- 3.3.1 Gaiatrons -- 3.3.2 AgroNode -- 3.3.3 SensLog and Data Connectors -- 3.3.4 Mobile/Machinery Sensors -- References -- 4 Remote Sensing -- 4.1 Introduction -- 4.2 Earth Observation Relation to Big Data -- 4.3 Data Formats, Storage and Access -- 4.3.1 Formats and Standards -- 4.3.2 Data Sources -- 4.4 Selected Technologies -- 4.4.1 Metadata Catalogue , 4.4.2 Object Storage and Data Access -- 4.5 Usage of Earth Observation Data in DataBio's Pilots -- References -- 5 Crowdsourced Data -- 5.1 Introduction -- 5.2 SensLog VGI Profile -- 5.3 Maps as Citizens Science Objects -- References -- 6 Genomics Data -- 6.1 Introduction -- 6.2 Genomic and Other Omics Data in DataBio -- 6.3 Genomic Data Management Systems -- References -- Part III Data Integration and Modelling -- 7 Linked Data and Metadata -- 7.1 Introduction -- 7.2 Metadata -- 7.3 Linked Data -- 7.4 Linked Data Best Practices -- 7.5 The Linked Open Data (LOD) Cloud , 7.6 Enterprise Linked Data (LED) -- References -- 8 Linked Data Usages in DataBio -- 8.1 Introduction -- 8.2 Linked Data Pipeline Instantiations in DataBio -- 8.2.1 Linked Data in Agriculture Related to Cereals and Biomass Crops -- 8.2.2 Linked Sensor Data from Machinery Management -- 8.2.3 Linked Open EU-Datasets Related to Agriculture and Other Bio Sectors -- 8.2.4 Linked (Meta) Data of Geospatial Datasets -- 8.2.5 Linked Fishery Data -- 8.3 Experiences from DataBio with Linked Data -- 8.3.1 Usage and Exploitation of Linked Data -- 8.3.2 Experiences in the Agricultural Domain , 8.3.3 Experiences with DBpedia , English
    Additional Edition: ISBN 3-030-71068-8
    Language: English
    Keywords: Llibres electrònics
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    UID:
    b3kat_BV036710467
    Format: 1 Online-Ressource (XII, 155 S.) , graph. Darst.
    ISBN: 9783642158766 , 9783642158773
    Series Statement: Lecture notes in computer science 6369
    Note: Literaturangaben
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Internet ; Netzwerktopologie ; Serviceorientierte Architektur ; Konferenzschrift ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    Library Location Call Number Volume/Issue/Year Availability
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  • 7
    UID:
    gbv_1778405606
    Format: 1 Online-Ressource (423 p.)
    ISBN: 9783030710699
    Content: This edited open access book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources. As a European initiative, the goal is to use these new findings to support decision-makers and producers – meaning farmers, land and forest owners and fishermen. With their 27 pilot projects from 17 countries, the authors examine important sectors and highlight examples where modern data-driven methods were used to increase sustainability. How can farmers, foresters or fishermen use these insights in their daily lives? The authors answer this and other questions for our readers. The first four parts of this book give an overview of the big data technologies relevant for optimal raw material gathering. The next three parts put these technologies into perspective, by showing useable applications from farming, forestry and fishery. The final part of this book gives a summary and a view on the future. With its broad outlook and variety of topics, this book is an enrichment for students and scientists in bioeconomy, biodiversity and renewable resources
    Note: English
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 8
    UID:
    almahu_BV036687764
    Format: XII, 155 S. : , graph. Darst. ; , 24 cm.
    ISBN: 978-3-642-15876-6
    Series Statement: Lecture notes in computer science 6369 : Services science
    Note: Literaturangaben
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Internet ; Netzwerktopologie ; Serviceorientierte Architektur ; Konferenzschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 9
    UID:
    gbv_1832315894
    Format: 1 Online-Ressource (544 p.)
    ISBN: 9783030783075
    Content: This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
    Note: English
    Language: Undetermined
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    UID:
    kobvindex_HPB1313606104
    Format: 1 online resource : , illustrations (chiefly color)
    ISBN: 9783030783075 , 3030783073
    Content: This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
    Note: Technologies and Applications for Big Data Value -- Part I: Technologies and Methods -- Trade-Offs and Challenges of Serverless Data Analytics -- Big Data and AI Pipeline Framework: Technology Analysis from a Benchmarking Perspective -- An Elastic Software Architecture for Extreme-Scale Big Data Analytics -- Privacy-Preserving Technologies for Trusted Data Spaces -- Leveraging Data-Driven Infrastructure Management to Facilitate AIOps for Big Data Applications and Operations -- Leveraging High-Performance Computing and Cloud Computing with Unified Big-DataWorkflows: The LEXIS Project -- Part II: Processes and Applications -- The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures -- Applying AI to Manage Acute and Chronic Clinical Condition -- 3D Human Big Data Exchange Between the Healthcare and Garment Sectors -- Using a Legal Knowledge Graph for Multilingual Compliance Services in Labor Law, Contract Management, and Geothermal Energy -- Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case -- Data-Driven Artificial Intelligence and Predictive Analytics for the Maintenance of Industrial Machinery with Hybrid and Cognitive Digital Twins -- Big Data Analytics in the Manufacturing Sector: Guidelines and Lessons Learned Through the Centro Ricerche FIAT (CRF) Case -- Next-Generation Big Data-Driven Factory 4.0 Operations and Optimization: The Boost 4.0 Experience -- Big Data-Driven Industry 4.0 Service Engineering Large-Scale Trials: The Boost 4.0 Experience -- Model-Based Engineering and Semantic Interoperability for Trusted Digital Twins Big Data Connection Across the Product Lifecycle -- A Data Science Pipeline for Big Linked Earth Observation Data -- Towards Cognitive Ports of the Futures -- Distributed Big Data Analytics in a Smart City -- Processing Big Data in Motion: Core Components and System Architectures with Applications to the Maritime Domain -- Knowledge Modeling and Incident Analysis for Special Cargo.
    Additional Edition: 3030783065
    Additional Edition: 9783030783068
    Language: English
    Keywords: Electronic books. ; Electronic books.
    Library Location Call Number Volume/Issue/Year Availability
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