Project Description: 

ROOT is a general-purpose framework that provides an object oriented set of tools with all the functionality needed to handle and analyze large amounts of data in an extremely efficient way. It defines the data as a set of objects, and then specialized storage methods are used to get direct access to the separate attributes of the selected objects, without having to touch the bulk of the data. Included in the framework are histograming methods in an arbitrary number of dimensions, curve fitting, function evaluation, minimization, graphics and visualization classes to allow the easy setup of an analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework that can considerably speed up any data analysis process.


Related Publications

•  R. Brun, F. Rademakers, ROOT — An object oriented data analysis framework, Nucl. Instr. and Methods in Physics A 389, Issues 1–2, 11 April 1997, (81-86),


• I. Antcheva, et al, ROOT — A C++ framework for petabyte data storage, statistical analysis and visualization, Computer Phys. Com., 180, Issue 12, December 2009, (2499-2512), (


Some projects using this technology: 
  • SAFETYN: General Aviation Safety & CERN KT
    In 2018, the start-up SAFETYN SaS joined InnoGEX, the French BIC of CERN technologies.
  • CERN experts shared their expertise on machine learning with Sanofi Pasteur
    A team of experts from CERN shared their expertise on machine learning with Sanofi Pasteur, the vaccines business unit of Sanofi, a global life sciences company.
  • GeneROOT: From High-Energy Physics to Large Genomics Datasets
    GeneROOT uses a data-processing framework developed at CERN for the high-energy physics community, to analyse large genomics datasets.

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