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Vision of Agriculture Systems in Area of Big Data

Karel Charvat

(Submission #293)


Abstract

The agriculture sector is of strategic importance for European society and economy. Due to its complexity, agrifood operators have to manage many different and heterogeneous sources of information. Agriculture requires collection, storage, sharing and analysis of large quantities of spatially and non-spatially referenced data. These data flows currently present a hurdle to uptake of precision agriculture as the multitude of data models, formats, interfaces and reference systems in use result in incompatibilities. In order to plan and make economically and environmentally sound decisions a combination and management of information is needed. Big data is moving into agriculture in a big way. Number of new technologies is influencing now farming: Sensors on fields and crops are starting to provide data points on soil conditions, as well as detailed info on wind, fertilizer requirements, water availability and pest infestations, GPS units on tractors, can help determine optimal usage of agriculture machinery, Unmanned aerial vehicles, or drones, can patrol fields and alert farmers to crop ripeness or potential problems, RFID-based traceability systems can provide a constant data stream on farm products as they move through the supply chain, from the farm to the compost or recycle bin. Individual plants can be monitored for nutrients and growth rates. Big data technology (BDT) is a new technological paradigm that is driving the entire economy, including low-tech industries such as agriculture where it is implemented under the banner of precision farming (PF). But there is necessary to mentioned, that farmers primary focused not on (big) data, but on knowledge generated from this data. For every discussion about knowledge or information management it is important to better understand basic terms such as data, information and knowledge. For better explanation we will use Data-Information-Knowledge-Wisdom hierarchy Ackoff including Data: as symbols; Information: data that are processed to be useful; provides answers to "who", "what", "where", and "when" questions; Knowledge: application of data and information; answers "how" questions and Wisdom: evaluated understanding. Presentation will be focused on new way, how agriculture data could be shared, analysed and visualised and how different business models could by apply.

Categories

Topic Area:  [1.11] Agriculture - forestry - aquaculture
Abstract Type:  Oral Presentation and paper in IJSDIR

Additional Fields

 
Academic:   Yes
 
Data Provider:   Yes
 
Data User:   Yes
 
INSPIRE Implementer (IT):   Yes
 
INSPIRE newbies:   Yes
 
Policy Officers:   Yes
 
Public Administration (MS/Regional/Local):   Yes
 
Thematic specialists:   Yes

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