The main vision of the ScaleAGData project is to obtain insights in how the complex data streams should be governed and organized, as well as to develop the data technology (from data streaming, data analytics and AI (Artificial Intelligence) applications) needed to scale data collected at the farm level to regional datasets built for agri-environmental monitoring and the management of agricultural production. 


ScaleAgData is about 

  • insights in governance of complex data streams 

  • upscaling agri-data 

  • innovation in sensor technology, data analytics & EO product 
    for a European-wide monitoring of agri-environmental conditions. 

It will contribute to the overall competitiveness and sustainability  performance of the European agricultural sector  

  • enabling the assessment of the innovations and data governance frameworks 

  • demonstrating added values of improved monitoring capabilities  for a range of users 

We define 5 main objectives:

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1. Developing innovative approaches for collection in-situ data and applying data technologies by actively involving each stakeholder in the agricultural production process

ScaleAgData aims to further develop proximal sensing technologies to collect data on fields in view of enhancing the capacities of smart farming and environmental monitoring. 
Data from in-situ sensors provide essential information on what is needed in the entire agricultural production process, and therefore the degree of smart farming in larger regions. 

2. Enabling and promoting data sharing along the entire data value chain

ScaleAgData will address the issues of data sharing and data governance, including governance models, metadata architecture, data formats, space connectivity, quality control as well as data privacy governance. Awareness of the how and why of data sharing in agriculture will be raised. 

3. Demontrating how the readily accessible , locally collected sensor data can be scaled to agri-environmental data products at the national, regional, or European level

A variety of data integration methods will be used to develop multiple innovative data integration and upscaling methodologies which increase the performance of existing data products (spatial, temporal, and thematic) and enable the development of new data products. 

4. Demonstrating the benefit of the improved monitoring capacities of the agri-environmental conditions in a precision farming context

ScaleAgData aims at providing insights and lessons learned on how these improved data products can be used by farmers to further improve their production process. 

5. Demonstrating the benefit of upscaled regional datasets for the agricultural sector in general

Because better information on the agri-environmental conditions over larger areas is of interest to a wide range of stakeholders, ScaleAgdata aims at providing insights on how these improved monitoring capacities can be used to the benefit of these stakeholders, through an active participation along the data value chain.