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UBITECH undertakes the technical coordination of the CYBELE Innovation Action on HPC-enabled, scalable Big Data analytics for precision agriculture and livestock farming

UBITECH participates in the kick-off meeting, in Barcelona, Spain (January 28-30, 2019) of the CYBELE Innovation Action, officially started on January  1st, 2019. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 825355) and spans on the period January 2019 – December 2021. CYBELE aspires at demonstrating how the convergence of HPC, Big Data, Cloud Computing and the IoT can revolutionize farming, reduce scarcity and increase food supply, bringing social, economic, and environmental benefits. CYBELE intends to safeguard that stakeholders have integrated, unmediated access to a vast amount of large scale datasets of diverse types from a variety of sources, and they are capable of generating value and extracting insights, by providing secure and unmediated access to large-scale HPC infrastructures supporting data discovery, processing, combination and visualization services, solving challenges modelled as mathematical algorithms requiring high computing power.

In this context, UBITECH will undertake the responsibility of the technical coordination of CYBELE towards the realization of large scale HPC-enabled test beds and delivers a distributed big data management architecture and a data management strategy providing 1) integrated, unmediated access to large scale datasets of diverse types from a multitude of distributed data sources, 2) a data and service driven virtual HPC-enabled environment supporting the execution of multi-parametric agri-food related impact model experiments, optimizing the features of processing large scale datasets and 3) a bouquet of domain specific and generic services on top of the virtual research environment facilitating the elicitation of knowledge from big agri-food related data, addressing the issue of increasing responsiveness and empowering automation-assisted decision making, empowering the stakeholders to use resources in a more environmentally responsible manner, improve sourcing decisions, and implement circular-economy solutions in the food chain.

Moreover, UBITECH R&D team will drive the implementation of a dedicated Experiment Composition Environment, enabling simulation execution in the Precision Agriculture and Precision Livestock Farming domains, that aims to facilitate the detaching of the design, development and execution of the big data analysis processes, supporting embedded scientific computing and reproducible research. The analysis process will be based on the selection of an analysis template, where each analysis template will represent a specific algorithm with the associated software and execution endpoint, and will provide to the user the flexibility to adjust the relevant configuration parameters, including input parameters for the algorithm, execution parameters, parameters associated with networking and computing resources constraints, as well as output parameters. The Experiment Composition Environment will support the design and implementation of data analysis workflows, consisted of a series of data analysis processes, interconnected among each other in terms of input/output data streams/objects. The analytics workflows designed, will be sent for execution on well-known HPC and Big Data frameworks, which will run on HPC resources abstracted to the user.