Big Data in Bioeconomy : Results from the European DataBio Project

• Autore: Södergård Caj
• Pubblicazione: Cham, : Springer International Publishing AG, 2021
• Descrizione fisica: 1 online resource (416 p.)
• Soggetto topico: Forestry & silviculture: practice & techniques; Agricultural science; Databases; Environmental economics; Dades massives; Biologia econòmica
• Soggetto genere / forma: Llibres electrònics
• Soggetto non controllato: Data-driven bioeconomy; big data; artificial intelligence; agriculture; forestry; earth observation; satellite images; fishery; open access
• Altri autori: MildorfTomas HabyarimanaEphrem BerreArne J FernandesJose A Zinke-WehlmannChristian
• Note generali: Description based upon print version of record.
• Nota di contenuto: 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
• Sommario/riassunto: 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.
• Titolo autorizzato: Big Data in Bioeconomy
• ISBN: 3-030-71069-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910494568803321
• Lo trovi qui: Univ. Federico II