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MooViE - Engine for single-view visual analysis of multivariate data

Anton StratmanniD, Martin BeyßiD, Johann F. JadebeckiD, Katharina NöhiD

Abstract

SummaryUnderstanding input-output relationships within multivariate datasets is an ubiquitous task in the life and data sciences. For this, visual analysis is indispensable for providing expressive summaries and preparing decision-making. We present the visual analysis approach and software MooViE, which is designed to strike the balance between being tailored to the specific data semantic and while being broadly applicable. MooViE supports the data exploration process for extracting important information from the data and captures the result in a fresh single-view visualization. MooViE is implemented in C++ to facilitate fast access and effective interaction with comprehensive multivariate datasets. We showcase the engine for various application fields, relevant to the life sciences. Availability and ImplementationThe source code is available under MIT license at https://jugit.fz-juelich.de/IBG-1/ModSim/MooViE and https://github.com/JuBiotechMooViE, with detailed documentation and usage instructions (https://moovie.readthedocs.io), as well as zenodo-archived releases (https://doi.org/10.5281/zenodo.10997388). Platform independent Docker images are also available (jugit-registry.fz-juelich.de/ibg-1/modsim/moovie/moovie). ContactKatharina Noh k.noeh@fz-juelich.de

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02 /Specification & Classification

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