Big Data in Bioeconomy

Results from the European DataBio Project
1. Auflage 2021
ISBN: 978-3-030-71068-2
Verlag: Springer

Buch, Englisch, 423 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 909 g

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.

Zielgruppe

Graduate

Autoren/Hrsg.

Södergård, Caj

Mildorf, Tomas

Habyarimana, Ephrem

Berre, Arne J.

Fernandes, Jose A.

Zinke-Wehlmann, Christian

Fachgebiete

• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Primärer Sektor Agrarökonomie, Ernährungswirtschaft
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
• Naturwissenschaften Agrarwissenschaften Ackerbaukunde, Pflanzenbau Forstwirtschaft, Forstwissenschaft
• Wirtschaftswissenschaften Volkswirtschaftslehre Umweltökonomie

Inhaltsverzeichnis

Terms, Acronyms and Abbreviations

Foreword  (PO or Director Data at European Commission- DG CONNECT)

Introduction to the book and the project & acknowledgements (Editors, Thanasis)

 

Part I – Technological Foundation: Big Data Technologies for BioIndustries 

Chapter 1: State of the art of technology and market potential (Caj Södergård/VTTet al) 

Chapter 2: Standards (Ingo Simonis/OGC et al)

Chapter 3 : Sensor Data (Savvas Rogotis/NP et al)

Chapter 4: Geospatial Data (Eva Klien /Fraunhofer et al)

Chapter 5: Crowdsourced Data (Karel Charvat/Lespro)

Chapter 6 : Genomics Data (Ephrem Habyarimana/CREA et al)

Chapter 7:Integrating data sources with Linked Data (Christian Zinke-Wehlmann/Infai et al)

Chapter 8: Linked Data usages in DataBio (Christian Zinke-Wehlmann/Infai et al)

Chapter 9:Data Pipelines: Modelling and Evaluation ofmodels (Kais Chaabouni)/Softeam et al

Chapter 10: Data Analytics and Machine Learning(Pekka Siltanen/VTT et al)

Chapter 11:  Real Time Data Processing (Fabiana Fournier/IBM, et al)

Chapter 12: Privacy Preserving Analytics, Processing and Data Management (Baldur Kubo/Cybernetica)

Chapter 13: Data Visualisation (Eva Klien/Fraunhofer et al)

Part II – Applications in Agriculture               

                Chapter 14:  What is Smart Agriculture (Ephrem Habyarimana/CREA, Christian Zinke-Wehlmann/Infai)

Chapter 15: NP’s Smart farming pilots (Savvas Rogotis/NP).

Chapter 16: Big Data assets applied to the calculation of Irrigation needs in large scale Irrigation Communities (Iluminada Sevilla/Tragsa et al)

               Chapter 17: Genomics Biomass pilots (Ephrem Habyarimana/CREA et al)

Chapter 18: Yield estimation in Sorghum and Cultivated Potato (Ephrem Habyarimana/CREA, Nicole

Bartelds/NB Advies)

Chapter 19:Yield variability  mapping (Karel Charvat, Lespro et al)

Chapter 20: Farm Weather Insurance Assessment (Antonella Catucci/e-Geos).  

Chapter 21: Copernicus Data and CAP Subsidies Control (Olimpia Copacenaru

       /Terrasigna et al)

Chapter 22: Future vision, Summary and Outlook

 

Part III – Applications in Forestry           

Chapter 23: State of the art of technology and market potential (Jukka 

Miettinen/VTT)

Chapter 24: Finnish Forest Data based Metsään.fi-services (Virpi Stenman/Metsäkeskus)

               Chapter 25: Forest variable estimation and change monitoring by Big Data remote

sensing ( Jukka Miettinen/VTT et al)

Chapter 26: Monitoring Forest Health: Big Data applied to diseases and plagues control (María Jose

Checa et al/Tragsa)

Chapter 27: Forest damage monitoring for the bark beetle (Petr Lukeš/ FMI)                  

Chapter 28: Future Vision, Summary of Big Data in Forestry (Jukka Miettinen/VTT et al)                        

Part IV – Applications in Fishery              

Chapter 29: State of the art of technology and market potential (Karl-Johan Reite /SINTEF et al)

Chapter 30: Tuna Fisheries (Iñaki Quincoces/AZTI et al)

Chapter 31: Small pelagic fisheries (K.G.A/SINTEF et al)

Chapter 32: Future Vision, Summary and Outlook (Josean Fernandes/AZTI et al)

Part V – Summary and Outlook

Chapter 33: Summary of Potential of Big Data Technology 

Chapter 34: Outreach, Perspective, Exploitation

Chapter 35: How can I apply Big Data?

Über Autor(innen)

About the Editors:

Dr Caj Södergård is Research Professor at VTT and Dr. Tech. from Helsinki University of Technology. He has worked as machine vision designer at Decon Oy and as Scientist, Senior Scientist and Area Manager at VTT. He has focused on processing and analysis of big data in media, learning, nutrition, environment and bioeconomy. He has 260 publications and 5 patents. He was in the European High Level Expert Group on Open Science Cloud. He is on the Board for Big Data Value Association and was Chair of the European Big Data Value Forum 2019. He was Technical Manager of DataBio.

 Dr Tomas Mildorf is a researcher at the Department of Geomatics at the University of West Bohemia, Czech Republic. Tomas is responsible for European research projects, their management and scientific lead. The main thematic domains include agriculture, rural development, transport and spatial planning. Tomas is the chairman of the Plan4all association and is involved in activities of the Group on Earth Observations, Big Data Value Association and the Open Geospatial Consortium.

 Dr Ephrem Habyarimana, Ir, MS, MS, MASt, PhD, a Research Scientist at CREA, Italy, has documented skills and expertise of more than 25 years in agronomy, crop science, genetics and plant breeding integrating diverse technologies i.e., agroecological and genomic modelling, big data analytics e.g., phenomics, genomics for the sustainable crop improvement. He trained in North and Latin America, Africa, Asia, and Europe, authored 40+ scientific papers; is inventor: DeepTech innovations, European DataSci & Artificial Intelligence Awards finalist, co-author of 5 sorghum varieties.

 Dr. Arne J. Berre is Chief Scientist at SINTEF Digital and is Innovation Director at the Norwegian Center for AI Innovation (NorwAI). His PhD is from NTNU in 1993 is on the topic of Systems Interoperability.  He is the leader of the BDVA TF6 on Technical priorities and is involved in ISO SC42 on AI and Big Data.  He was responsible for the platform reference model in the DataBio project. He has been in the technical lead of more than 20 European projects and has more than 100 scientific publications.

 Dr. Jose A. Fernandes is a scientist from computing and artificial intelligence studies with the skills and experience needed to translate the data into valuable information for marine research. These skills are curiosity, multidisciplinary communicative, biological, oceanographic, economic, statistics and machine learning expertise. Current line of research is about mitigation of impacts and long-term sustainability of fisheries using the above skills. He has over 120 publications, 40 in scientific publications in high impact journals.

 Dr Christian Zinke-Wehlmann is a research group leader for “Efficient Technology Integration” at the Institute for Applied Informatics at the University of Leipzig. Working at the edge of technology, work, and service systems, he became a doctor in 2017. His research concentrates on Linked Data, Data Analytics, Data Visualisation, Service Engineering and Management, as well as Knowledge Management. This expertise is represented in this publication and in more than 40 other publications.