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Titlebook: Big Data in Bioeconomy; Results from the Eur Caj S?derg?rd,Tomas Mildorf,Christian Zinke-Wehlma Book‘‘‘‘‘‘‘‘ 2021 The Editor(s) (if applica

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發(fā)表于 2025-3-21 19:16:39 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Big Data in Bioeconomy
期刊簡(jiǎn)稱Results from the Eur
影響因子2023Caj S?derg?rd,Tomas Mildorf,Christian Zinke-Wehlma
視頻videohttp://file.papertrans.cn/186/185696/185696.mp4
發(fā)行地址This book is open access, which means that you have free and unlimited access.Explains how Big Data Technology can make raw material gathering more efficient and sustainable.Shows how common software
圖書封面Titlebook: Big Data in Bioeconomy; Results from the Eur Caj S?derg?rd,Tomas Mildorf,Christian Zinke-Wehlma Book‘‘‘‘‘‘‘‘ 2021 The Editor(s) (if applica
影響因子.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 andfishery. 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 a
Pindex Book‘‘‘‘‘‘‘‘ 2021
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發(fā)表于 2025-3-21 20:25:20 | 只看該作者
ng more efficient and sustainable.Shows how common software .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 a
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發(fā)表于 2025-3-22 02:48:48 | 只看該作者
Kleene Languages and Finite Automata which purpose. These associated features make the data more interpretable and assist in turning it into useful information. This chapter briefly introduces the concepts of metadata and Linked Data—highly structured and interlinked data, their standards and their usages, with some elaboration on the role of Linked Data in bioeconomy.
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Lenore E. A. Walker,David L. Shapiro. Next, we present an overview of representative software technologiesfor efficiently describing, storing, querying and accessing Earth Observation datasets. The chapter concludes with a summary of the Earth Observation datasets used in each DataBio pilot.
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發(fā)表于 2025-3-22 16:32:18 | 只看該作者
Clinical Assessment in Forensic Settingssualize SensLog data. SensLog data model builds on the Observations & Measurements conceptual model from ISO 19156 and includes additional sections, e.g., for user authentication or volunteered geographic information (VGI) collection. It uses PostgreSQL database with PostGIS for data storage and several API endpoints.
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發(fā)表于 2025-3-22 18:25:02 | 只看該作者
https://doi.org/10.1007/978-3-662-03809-3ese pipelines is to automate as much as possible the process to transform and publish different input datasets as Linked Data. In this chapter, we describe these pipelines and how they were applied to support different uses cases in the project, including the tools and methods used to implement them.
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發(fā)表于 2025-3-23 04:14:10 | 只看該作者
Remote Sensing. Next, we present an overview of representative software technologiesfor efficiently describing, storing, querying and accessing Earth Observation datasets. The chapter concludes with a summary of the Earth Observation datasets used in each DataBio pilot.
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發(fā)表于 2025-3-23 06:26:05 | 只看該作者
Crowdsourced Datasualize SensLog data. SensLog data model builds on the Observations & Measurements conceptual model from ISO 19156 and includes additional sections, e.g., for user authentication or volunteered geographic information (VGI) collection. It uses PostgreSQL database with PostGIS for data storage and several API endpoints.
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