Big Data Technologies in DataBio

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F21%3A43962861" target="_blank" >RIV/49777513:23520/21:43962861 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-71069-9_1" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-71069-9_1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-71069-9_1" target="_blank" >10.1007/978-3-030-71069-9_1</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Big Data Technologies in DataBio

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Big Data Technologies in DataBio

Popis výsledku anglicky

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.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Big Data in Bioeconomy: Results from the European DataBio Project

ISBN

978-3-030-71069-9

Počet stran výsledku

13

Strana od-do

3-15

Počet stran knihy

423

Název nakladatele

Springer

Místo vydání

Cham, Switzerland

Kód UT WoS kapitoly

—