Big Data Technologies in DataBio

Caj Södergård (Corresponding author), Tomas Mildorf, Arne J. Berre, Aphrodite Tsalgatidou, Karel Charvát

Research output: Chapter in Book/Report/Conference proceedingChapter or book articleScientificpeer-review

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.
Original languageEnglish
Title of host publicationBig Data in Bioeconomy
Subtitle of host publicationResults from the European DataBio Project
EditorsCaj Södergård, Tomas Mildorf, Ephrem Habyarimana, Arne J. Berre, Jose A. Fernandes, Christian Zinke-Wehlmann
PublisherSpringer
Chapter1
Pages3-15
ISBN (Electronic)978-3-030-71069-9
ISBN (Print)978-3-030-71068-2
DOIs
Publication statusPublished - 14 Aug 2021
MoE publication typeA3 Part of a book or another research book

Keywords

  • big data
  • big data pipelines
  • reference model
  • data analytics
  • DataBio platform
  • open data
  • FAIR data
  • Data-driven AI

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