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Information sources in agriculture

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F24%3A100914" target="_blank" >RIV/60460709:41110/24:100914 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.17221/361/2024-PSE" target="_blank" >https://doi.org/10.17221/361/2024-PSE</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.17221/361/2024-PSE" target="_blank" >10.17221/361/2024-PSE</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Information sources in agriculture

  • Popis výsledku v původním jazyce

    The aim of this study is to define data sources and propose methods for effective and secure data management in an agricultural enterprise in the context of using data for decision support. Current developments in information and communication technology (ICT) have contributed towards the increase in the amount of generated data in various fields. The main data sources for agricultural enterprises are the farm itself, suppliers, government, market, and research. The use of smart solutions, artificial intelligence, and other innovative practices in agriculture is discussed at many conferences, in various journals, strategies and project plans. Data is the essential raw material for all these solutions. Large amounts of data cannot be analysed efficiently with spreadsheet programs. Currently, there are trends in the use of data, for example, in business intelligence (decision-making systems), e.g. tools using online transaction processing (OLAP) or process automation or the possibility of e.g. tracing the origin of food. The availability and possibility of creating large data sets bring many challenges related to managing that data. To effectively manage farm data, it is essential to have a well-developed data management plan (DMP) used to formalise the processes related to handling. A DMP mainly addresses archiving, backup, licensing and other important aspects of data management. The challenges and developments in farm data management include incorporating artificial intelligence into data analysis and security. Food is classified as an "Entity of Critical Importance" in the NIS2 EU Directive, which also deals with cybersecurity issues.

  • Název v anglickém jazyce

    Information sources in agriculture

  • Popis výsledku anglicky

    The aim of this study is to define data sources and propose methods for effective and secure data management in an agricultural enterprise in the context of using data for decision support. Current developments in information and communication technology (ICT) have contributed towards the increase in the amount of generated data in various fields. The main data sources for agricultural enterprises are the farm itself, suppliers, government, market, and research. The use of smart solutions, artificial intelligence, and other innovative practices in agriculture is discussed at many conferences, in various journals, strategies and project plans. Data is the essential raw material for all these solutions. Large amounts of data cannot be analysed efficiently with spreadsheet programs. Currently, there are trends in the use of data, for example, in business intelligence (decision-making systems), e.g. tools using online transaction processing (OLAP) or process automation or the possibility of e.g. tracing the origin of food. The availability and possibility of creating large data sets bring many challenges related to managing that data. To effectively manage farm data, it is essential to have a well-developed data management plan (DMP) used to formalise the processes related to handling. A DMP mainly addresses archiving, backup, licensing and other important aspects of data management. The challenges and developments in farm data management include incorporating artificial intelligence into data analysis and security. Food is classified as an "Entity of Critical Importance" in the NIS2 EU Directive, which also deals with cybersecurity issues.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10200 - Computer and information sciences

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/QK23020058" target="_blank" >QK23020058: Precizní zemědělství a digitalizace v ČR</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2024

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název periodika

    Plant, Soil and Environment

  • ISSN

    1214-1178

  • e-ISSN

    1214-1178

  • Svazek periodika

    70

  • Číslo periodika v rámci svazku

    2024

  • Stát vydavatele periodika

    CZ - Česká republika

  • Počet stran výsledku

    7

  • Strana od-do

    712-718

  • Kód UT WoS článku

    001330460100001

  • EID výsledku v databázi Scopus

    2-s2.0-85207837851