Open Data Initiative

As part of PhotoMeca Association's commitment to advancing Open Data Science, this year’s conference encourages all participants to labellize their datasets when submitting abstracts. By clearly labeling and documenting your datasets, you contribute to greater transparency, reproducibility, and collaboration within the research community.

Applying for the labellization of the dataset associated to a contribution is simple: 

• Fill out our online form[link], which will automatically generate a R3XA file for your dataset (see informations below).
• Add this file to the public repository of your dataset.
• Submit your abstract and mention the dataset in the text (see the templates).
• Check the option "Apply for data labellization" in the submission form and provide the dataset URL (i.e. zenodo or any equivalent open archive).

The review process will include checks and validations of the submitted metadata, leading to the acceptance or rejection of the data labellization. Note that in order to be labellized, a dataset must be related to an accepted abstract !

Labellized datasets will be highlighted during the conference and featured in PhotoMecA's Open Data repository, fostering broader access and impact.

Join us in promoting open science—submit your abstract with a labellizable dataset!

About the R3XA format (Reference & R3XA Format Documentation).

The R3XA format (Reusable, Reproducible, and Replicable eXperimental data Archive) is designed to standardize the documentation of experimental datasets in mechanics and related fields. It emphasizes three core principles: Reusability, ensuring data can be easily accessed and repurposed by others; Reproducibility, providing sufficient metadata and context to replicate the experimental conditions and results; and Replicability, enabling independent verification of findings. The format structures metadata in a machine-readable way, capturing essential details such as experimental setup, instrumentation, environmental conditions, and data processing steps. The keywords for image data and DIC parameters also comply with the terminology of the iDICs Good Practices Guide. By adopting R3XA, researchers enhance the transparency, interoperability, and long-term value of their datasets, fostering collaboration and advancing open science.