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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 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.
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.
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.
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