Poster Open Access

Towards unified and reproducible processing of geoelectrical data

Weigand, Maximilian; Wagner, Florian M.

REDA - A Python package for reproducible electrical data analysis

The multitude of geoelectric measurement devices and inversion codes in use
is mirrored in a multitude of individually tailored data importing and
processing routines. The majority of scientific advancements in data processing
(e.g., filtering schemes, error estimation) is therefore not directly
transferable between use cases, especially when measurement devices and
inversion codes change. Reproducibility may be further impeded by the use of
commercial software such as MATLAB and Microsoft Excel.

To accelerate and concentrate scientific advancement and ensure reproducibility
of processing workflows, a unified framework for geoelectrical data processing
is required.  Based on the free and platform-compatible programming language
Python, we present a working prototype of such a unified interface and
demonstrate its functionality and ease of use by means of classical processing
workflow of geoelectrical time-lapse data (i.e., import, filtering, error
estimation, visualization, data export). Encompassing all functionality is a
journaling system which keeps track of all actions applied to the datasets,
thereby making the processing testable and reproducible. The framework is
designed to be as non-intrusive as possible, only to provide functionality
without forcing the user to follow a specific processing workflow. A variety of
importers and exporters is provided, so that the processing steps applied to
the data set do not depend on the measurement device and the inversion code
used thereafter.

We believe that the approach presented could foster exchange of best practices
and new techniques among academic groups and practitioners, and that a common
data import and export framework can ease the transition to fully reproducible
research. We welcome any feedback that could help in establishing such a tool
in the geoelectrical community.

The project is maintained on github:

Poster presented at the 4th International Workshop on Geoelectrical Monitoring (GELMON) 2017 in Vienna
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