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Processing and Visual Analyze of Heterogeneous and Multidimensional Data in Biomedical PLM Context

Abstract : The emergence of PLM for biomedical imaging lifecycle management highlights the needs for management and analysis of heterogeneous, complex and multidimensional data in PLM systems. Data provenance in biomedical imaging domain is complex, notably provenance of processing data, and to ensure full traceability in a purpose of reuse, processing operations must be integrated to PLM systems and processing provenance must be easily analyzable by users. The DIMP (Data Integrated Management and Processing) method was designed for this objective: it allows user to launch easily processing chains from PLM systems and ensures a full management of provenance. The MDG (Multidimensional Dynamic Graph) representation is introduced to formalize complex provenance and data relationships. JGEX (Json Graph EXchange) file format and NeuroGraphViewer web graph visualization client have been developed to facilitate the analysis of MDG. An application of the DIMP method to the study of functional brain connectivity through MDG analysis encourages further work on analysis of complex relationships in PLM systems.
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Submitted on : Friday, February 2, 2018 - 4:02:08 PM
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Marianne Allanic, Pierre-yves Hervé, Alexandre Durupt, Marc Joliot, Philippe Boutinaud, et al.. Processing and Visual Analyze of Heterogeneous and Multidimensional Data in Biomedical PLM Context. 13th IFIP International Conference on Product Lifecycle Management (PLM), Jul 2016, Columbia, SC, United States. pp.385-398, ⟨10.1007/978-3-319-54660-5_35⟩. ⟨hal-01699675⟩



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