Project description
Smart data management and analysis
Growing amounts of research data require new computing solutions to manage increased data storage, utilisation, and analysis capabilities. The EU-funded SMARTHEP project will break from the traditional paradigm of ‘first collect data, then analyse it’ and move towards real-time analysis (RTA) where data collection and analysis become synonymous, so that unprocessed information that would be expensive to store can be discarded. As a consortium formed by academic and industrial partners on scientific, technological, and entrepreneurship aspects of RTA, the project will train a new generation of inter-sector researchers and give them the tools to process large datasets in real-time, aided by machine learning and hybrid computing architectures.
Objective
SMARTHEP is a consortium formed by academic and industrial partners on scientific, technological, and entrepreneurship aspects of real-time analysis. The focus of SMARTHEP is a central question in a data-rich environment: how to make the most of the available data to take decisions fast and efficiently, making the most of the available data. The main purpose of SMARTHEP is to train a new generation of inter-sector researchers and give them the tools to tackle this challenge, by processing large datasets in real- time, aided by Machine Learning and hybrid computing architectures. The results of SMARTHEP will benefit the HEP community in providing cutting edge technology and algorithms for the area of data selection (triggering) and particle detection, leading to precise measurement of the fundamental constituents of matter and enabling the discovery of new physics processes. The results of SMARTHEP include concrete commercial deliverables for industry in the fields of transport, finance and industrial decision-making processes. The training aspect of this work is crucial to SMARTHEP. The young investigators working within SMARTHEP will also be prepared as professionals in the upcoming and highly demanded area of Data Science. They will have the chance to gather work experiences and training in industry during their PhD degree and establish connections to companies, as well as acquire the skills that are necessary to a career in either industry or academia.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Programme(s)
Coordinator
M13 9PL Manchester
United Kingdom