12 results on '"Fernandes, Jose A."'
Search Results
2. Big Data in Bioeconomy
- Author
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Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne J., Fernandes, Jose A., and Zinke-Wehlmann, Christian
- Subjects
Data-driven bioeconomy ,big data ,artificial intelligence ,agriculture ,forestry ,earth observation ,satellite images ,fishery ,open access ,bic Book Industry Communication::T Technology, engineering, agriculture::TV Agriculture & farming::TVR Forestry & silviculture: practice & techniques ,bic Book Industry Communication::T Technology, engineering, agriculture::TV Agriculture & farming::TVB Agricultural science ,bic Book Industry Communication::U Computing & information technology::UN Databases ,bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics - Abstract
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.
- Published
- 2021
- Full Text
- View/download PDF
3. Sustainable and Added Value Small Pelagics Fisheries Pilots
- Author
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Reite, Karl-Johan, Haugen, J., Michelsen, F. A., Aarsæther, K. G., Södergård, Caj, editor, Mildorf, Tomas, editor, Habyarimana, Ephrem, editor, Berre, Arne J., editor, Fernandes, Jose A., editor, and Zinke-Wehlmann, Christian, editor
- Published
- 2021
- Full Text
- View/download PDF
4. Future Vision, Summary and Outlook
- Author
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Habyarimana, Ephrem, Södergård, Caj, editor, Mildorf, Tomas, editor, Habyarimana, Ephrem, editor, Berre, Arne J., editor, Fernandes, Jose A., editor, and Zinke-Wehlmann, Christian, editor
- Published
- 2021
- Full Text
- View/download PDF
5. Big Data Technologies in DataBio
- Author
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Södergård, Caj, Mildorf, Tomas, Berre, Arne J., Tsalgatidou, Aphrodite, Charvát, Karel, Södergård, Caj, editor, Mildorf, Tomas, editor, Habyarimana, Ephrem, editor, Berre, Arne J., editor, Fernandes, Jose A., editor, and Zinke-Wehlmann, Christian, editor
- Published
- 2021
- Full Text
- View/download PDF
6. Summary of Potential and Exploitation of Big Data and AI in Bioeconomy
- Author
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Caj Södergård, Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne J., Fernandes, Jose A., and Zinke-Wehlmann, Christian
- Subjects
Exploit ,Computer science ,business.industry ,Big data ,Enterprise architecture ,Linked data ,15. Life on land ,computer.software_genre ,Crowdsourcing ,Data science ,Data sharing ,ArchiMate ,business ,computer ,Data integration - Abstract
In this final chapter, we summarize the DataBio learnings about how to exploit big data and AI in bioeconomy. The development platform for the software used in the 27 pilots was a central tool. The Enterprise Architecture model Archimate laid a solid basis for the complex software in the pilots. Handling data from sensors and earth observation were shown in numerous pilots. Genomic data from crop species allows us to significantly speed up plant breeding by predicting plant properties in-silico. Data integration is crucial and we show how linked data enables searches over multiple datasets. Real-time processing of events provides insights for fast decision-making, for example about ship engine conditions. We show how sensitive bioeconomy data can be analysed in a privacy-preserving way. The agriculture pilots show with clear numbers the impact of big data and AI on precision agriculture, insurance and subsidies control. In forestry, DataBio developed several big data tools for forest monitoring. In fishery, we demonstrate how to reduce maintenance cost and time as well as fuel consumption in the operation of fishing vessels as well as how to accurately predict fish catches. The chapter ends with perspectives on earth observation, machine learning, data sharing and crowdsourcing.
- Published
- 2021
7. Big Data Visualisation
- Author
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Eva Klien, Caj Södergård, Miguel Angel Esbri, Javier Hitado, Karel Charvát, Christian Zinke-Wehlmann, Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne J., Fernandes, Jose A., and Zinke-Wehlmann, Christian
- Subjects
Geospatial analysis ,GPUs ,Computer science ,Big data ,0211 other engineering and technologies ,0507 social and economic geography ,02 engineering and technology ,computer.software_genre ,simplification and generalisation ,multidimensional ,Visualisation graphics ,021101 geological & geomatics engineering ,Focus (computing) ,Big data visualization ,Point (typography) ,business.industry ,05 social sciences ,Linked data ,Data science ,raster and vector tiling ,Visualization ,web clients ,Component-based software engineering ,linked open data ,time series ,business ,050703 geography ,computer ,3D - Abstract
In this chapter, we introduce the topic of big data visualization with a focus on the challenges related to geospatial data. We present several efficient techniques to address these challenges. We then provide examples from the DataBio project of visualisation solutions. These examples show that there are many technologies and software components available for big data visualisation, but they also point to limitations and the need for further research and development.
- Published
- 2021
8. Big Data Technologies in DataBio
- Author
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Aphrodite Tsalgatidou, Arne J. Berre, Caj Södergård, Karel Charvát, Tomas Mildorf, Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne J., Fernandes, Jose A., and Zinke-Wehlmann, Christian
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FAIR data ,Iterative and incremental development ,DataBio platform ,Computer science ,business.industry ,Data management ,Big data ,Software development ,open data ,reference model ,15. Life on land ,Data science ,Data sharing ,Software ,big data ,Data-driven AI ,Data analysis ,big data pipelines ,data analytics ,business ,Reference model - Abstract
In this introductory chapter, we present the technological background needed for understanding the work in DataBio. We start with basic concepts of Big Data including the main characteristics volume, velocity and variety. Thereafter, we discuss data pipelines and the Big Data Value (BDV) Reference Model that is referred to repeatedly in the book. The layered reference model ranges from data acquisition from sensors up to visualization and user interaction. We then discuss the differences between open and closed data. These differences are important for farmers, foresters and fishermen to understand, when they are considering sharing their professional data. Data sharing is significantly easier, if the data management conforms to the FAIR principles. We end the chapter by describing our DataBio platform that is a software development platform. It is an environment in which a piece of software is developed and improved in an iterative process providing a toolset for services in agriculture, forestry and fishery. The DataBio assets are gathered on the DataBio Hub that links to content both on the DataBio website and to Docker software repositories on clouds.
- Published
- 2021
9. Conclusions and Outlook—Summary of Big Data in Forestry
- Author
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Renne Tergujeff, Jukka Miettinen, Södergärd, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne, Fernandes, Jose, and Zinke-Wehlmann, Christian
- Subjects
Big data processing ,Service (business) ,business.industry ,business practices ,Big data ,platform connections ,Forestry ,15. Life on land ,Service provider ,Chain (unit) ,forest management practices ,Business ,value-adding chain - Abstract
In this chapter, we summarize the findings from the forestry pilots conducted during the DataBio project. Although the pilots demonstrated the functionality of big data in forestry through several practical applications and services, they also highlighted areas where further development is needed. More effort is needed particularly in ensuring smooth connections between the technical components of the processing pipelines, as well as designing the best business solutions within the big data service chain and between the service providers and users. Overall, the challenge for the coming years is to establish operational big data processing pipelines that meet the requirements and expectations of forestry stakeholders.
- Published
- 2021
10. Introduction—State of the Art of Technology and Market Potential for Big Data in Forestry
- Author
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Renne Tergujeff, Jukka Miettinen, Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne J., Fernandes, Jose A., and Zinke-Wehlmann, Christian
- Subjects
040101 forestry ,Data processing ,Earth observation ,010504 meteorology & atmospheric sciences ,business.industry ,Big data ,Forestry ,04 agricultural and veterinary sciences ,forest monitoring ,earth observation ,15. Life on land ,01 natural sciences ,forestry pilots ,Set (abstract data type) ,Market forces ,Market potential ,0401 agriculture, forestry, and fisheries ,State (computer science) ,forestry market ,business ,0105 earth and related environmental sciences - Abstract
Forest monitoring is undergoing rapid changes due to the growing data volumes, developing data processing technologies and increasing monitoring requirements. The DataBio forestry pilots set out to demonstrate how big data approaches can support the forestry sector to get full benefit of the evolving technologies and to meet the increasing monitoring requirements. In this introductory chapter, we describe underlying technical and market forces driving the forestry sector toward big data approaches, and give short overviews on the forestry pilots to be presented in the following chapters.
- Published
- 2021
11. Big Data in Bioeconomy:Results from the European DataBio Project
- Author
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Tomas Mildorf, Ephrem Habyarimana, Arne J. Berre, Caj Södergård, Jose A. Fernandes, Christian Zinke-Wehlmann, Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Fernandes, Jose A., and Zinke-wehlmann, Christian
- Subjects
2. Zero hunger ,open access ,Earth observation ,business.industry ,data-driven bioeconomy ,Environmental resource management ,Big data ,forestry ,earth observation ,15. Life on land ,artificial intelligence ,13. Climate action ,Agriculture ,big data ,fishery ,14. Life underwater ,Business ,SDG 7 - Affordable and Clean Energy ,satellite images ,agriculture ,SDG 15 - Life on Land - Abstract
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.
- Published
- 2021
12. Forest Variable Estimation and Change Monitoring Solutions Based on Remote Sensing Big Data
- Author
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Allan Aasbjerg Nielsen, Seppo Huurinainen, Renne Tergujeff, Stéphanie Bonnet, Jukka Miettinen, Södergård, Caj, Mildorf, Tomas, Habyarimana, Ephrem, Berre, Arne J., Fernandes, Jose A., and Zinke-Wehlmann, Christian
- Subjects
Estimation ,Service (systems architecture) ,Forest inventory ,010504 meteorology & atmospheric sciences ,business.industry ,Computer science ,Big data ,Transferability ,0207 environmental engineering ,Usability ,EO Regions! ,02 engineering and technology ,15. Life on land ,01 natural sciences ,Data science ,Variable (computer science) ,Remote sensing (archaeology) ,change monitoring ,Wuudis ,forest variable estimation ,020701 environmental engineering ,business ,0105 earth and related environmental sciences ,forestry TEP - Abstract
In this pilot, we demonstrate the usability of online platforms to provide forest inventory systems for exploiting the benefits of big data. The pilot highlights the technical transferability of online platform based forest inventory services. All of the services tested in the piloting sites were technically implemented successfully. However, in new geographical areas, strong user involvement in service definition and field data provision will be needed to provide reliable and meaningful results for the users. Overall, the pilot demonstrated well the benefits of technology use in forest monitoring through a range of forest inventory applications utilizing online big data processing approaches and inter-platform connections.
- Published
- 2021
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