| title: |
| PROVenance Patterns in Numerical Modelling and Finite Element Simulation Processes
of Bio-electric Systems |
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| in: |
| Sonderdruck aus: |
| 41st Annual International Conference of the IEEE Engineering in Medicine and Biology
Society (EMBC), Berlin, Germany, 2019 |
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pages 3377-3382
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|
IEEE, 2019
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| contributing persons: |
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| 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.
[English] |
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| document type: |
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| institution: |
| Faculty of Computer Science and Electrical Engineering |
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| language: |
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| subject class (DDC): |
| 004 Data processing Computer sciences |
| 621.3 Electrical Engineering, Electronics |
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| extent: |
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1 Online-Ressource (Seiten 3377-3382)
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publication /
production: |
Rostock
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Rostock: Universität Rostock
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|
2019
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| statement of responsibility: |
| Max Schröder, Hendrikje Raben, Frank Krüger, Andreas Ruscheinski, Ursula van Rienen,
Adelinde Uhrmacher, Sascha Spors |
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| identifiers: |
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| references: |
Erscheint auch als:
Verlags-Ausgabe
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| access condition: |
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| license/rights statement: |
all rights reserved
This work may only be used under the terms of the German Copyright Law (Urheberrechtsgesetz). |
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| RosDok id: |
rosdok_document_0000021686 |
| created / modified: |
09.03.2023 / 08.08.2023
|
| metadata license: |
The metadata of this document was dedicated to the public domain
(CC0 1.0 Universal Public Domain Dedication). |
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