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WelDX - Welding Data Exchange Format

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Overview

Scientific welding data covers a wide range of physical domains and timescales and are measured using various different sensors. Complex and highly specialized experimental setups at different welding institutes complicate the exchange of welding research data further.

The WelDX research project aims to foster the exchange of scientific data inside the welding community by developing and establishing a new open source file format suitable for the documentation of experimental welding data and upholding associated quality standards. In addition to fostering scientific collaboration inside the national and international welding community an associated advisory committee will be established to oversee the future development of the file format. The proposed file format will be developed with regard to current needs of the community regarding interoperability, data quality and performance and will be published under an appropriate open source license. By using the file format objectivity, comparability and reproducibility across different experimental setups can be improved.

The project is under active development by the Welding Technology division at Bundesanstalt für Materialforschung und -prüfung (BAM).

Installation

The WelDX package can be installed using conda or mamba package manager from the :code:conda-forge channel. These managers originate from the freely available Anaconda Python stack. If you do not have Anaconda or Miniconda installed yet, we ask you to install Miniconda-3. Documentation for the installation procedure can be found here. After this step you have access to the conda command and can proceed to installing the WeldX package.

conda install weldx -c conda-forge

The package is also available on pypi.

pip install weldx

Documentation

The full documentation is published on readthedocs.org. Click on one of the following links to get to the desired version:

Funding

This research is funded by the Federal Ministry of Education and Research of Germany under project number 16QK12.

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  • Python 78.1%
  • Jupyter Notebook 21.9%