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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書目名稱Big Data in Bioeconomy影響因子(影響力)




書目名稱Big Data in Bioeconomy影響因子(影響力)學科排名




書目名稱Big Data in Bioeconomy網(wǎng)絡公開度




書目名稱Big Data in Bioeconomy網(wǎng)絡公開度學科排名




書目名稱Big Data in Bioeconomy被引頻次




書目名稱Big Data in Bioeconomy被引頻次學科排名




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書目名稱Big Data in Bioeconomy年度引用學科排名




書目名稱Big Data in Bioeconomy讀者反饋




書目名稱Big Data in Bioeconomy讀者反饋學科排名

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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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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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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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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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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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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.