Big Data in Bioeconomy Results from the European DataBio Project
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...
| Autor principal: | |
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| Otros Autores: | , , , , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing AG
2021.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654182006719 |
Tabla de Contenidos:
- 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
