Data Warehouse and Decision Support on Integrated Crop Big Data

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Title: Data Warehouse and Decision Support on Integrated Crop Big Data
Authors: Ngo, Vuong M.Le-Khac, Nhien-AnKechadi, Tahar
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Date: 2020
Online since: 2020-12-11T10:37:09Z
Abstract: In recent years, precision agriculture is becoming very popular. The introduction of modern information and communication technologies for collecting and processing Agricultural data revolutionise the agriculture practises. This has started a while ago (early 20th century) and it is driven by the low cost of collecting data about everything; from information on fields such as seed, soil, fertiliser, pest, to weather data, drones and satellites images. Specially, the agricultural data mining today is considered as Big Data application in terms of volume, variety, velocity and veracity. Hence it leads to challenges in processing vast amounts of complex and diverse information to extract useful knowledge for the farmer, agronomist, and other businesses. It is a key foundation to establishing a crop intelligence platform, which will enable efficient resource management and high quality agronomy decision making and recommendations. In this paper, we designed and implemented a continental level agricultural data warehouse (ADW). ADW is characterised by its (1) flexible schema; (2) data integration from real agricultural multi datasets; (3) data science and business intelligent support; (4) high performance; (5) high storage; (6) security; (7) governance and monitoring; (8) consistency, availability and partition tolerant; (9) cloud compatibility. We also evaluate the performance of ADW and present some complex queries to extract and return necessary knowledge about crop management.
Funding Details: Science Foundation Ireland
Funding Details: Origin Enterprises Plc.
Type of material: Journal Article
Publisher: Inderscience
Journal: International Journal of Business Process Integration and Management
Keywords: Data warehouseDecision supportCrop Big DataSmart agriculture
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Language: en
Status of Item: Peer reviewed
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Appears in Collections:Computer Science Research Collection

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