Big Data in Bioeconomy : : Results from the European DataBio Project

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Big Data in Bioeconomy : : Results from the European DataBio Project

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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 t...

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Bibliographic Details
:
Södergård, Caj.
TeilnehmendeR:
Mildorf, Tomas.
Habyarimana, Ephrem.
Berre, Arne J.
Fernandes, Jose A.
Zinke-Wehlmann, Christian.
Year of Publication:2021
Language:English
Physical Description:1 online resource (416 p.)
Notes:Description based upon print version of record.
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Table of Contents:
  • 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

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