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Max Schröder     Hendrikje Raben     Frank Krüger     Andreas Ruscheinski     Ursula Rienen van     Adelinde Uhrmacher     Sascha Michael Spors

PROVenance Patterns in Numerical Modelling and Finite Element Simulation Processes of Bio-electric Systems

[Author manuscript version], Universität Rostock, 2019

in: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019 , pages 3377-3382, IEEE, 2019

Abstract: The reproducibility of scientific results gains increasing attention. In the context of biomedical engineering, this applies to experimental studies of three different kinds: in-vivo, in-vitro, and in-silico. Numerical modelling and finite element simulation of bio-electric systems are intricate processes involving manifold steps. A typical example of this process is the electrical stimulation at alloplastic reconstruction plates of the mandible. During the bio-electric modelling and simulation process, diverse methods realised in various software tools are exploited. To comprehensibly render how the final model has been developed requires a thorough documentation. We exploit the W3C provenance model PROV to structure this process and to make it accessible for modellers and for automatic analyses. Different entity types, such as data, model, software, literature, assumptions, and mathematical equations are distinguished; roles of entities within an activity are revealed as well as the involved researchers. In addition, we identify five process patterns: 1) information extraction from the literature; 2) generation of a geometrical model which uses data as input; 3) composition of several geometrical or mathematical models into a combined model; 4) parameterisation, which augments the input model by additional properties; and, finally, 5) refinement, which uses a model in addition to an assumption and generates an enhanced model. By modelling provenance information of a typical bio-electric modelling and simulation process as well as identifying provenance patterns, we provide a first step towards a better documentation of academic investigations in that scientific field.

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