DRAGON 0.1 open beta is released!

The first beta version of the MONSTER group’s MATLAB tool for Digital Reconstruction of Ancient Graphical ODFs (eNabling quantitative comparative analysis), also known as DRAGON, was released for an open beta test. DRAGON allows for the digitization of ODFs represented as pole figures in literature for use quantitatively, even if the original quantitative data is no longer available.

The code is available at: https://github.com/MONSTERgroup/DRAGON,

and the code for the open beta research study is available here: https://github.com/MONSTERgroup/DRAGON/tree/Study.

If you wish to participate in the study, the study response questionnaire is here: https://ufl.qualtrics.com/jfe/form/SV_3mTGayJqF1XllA2

In order to accommodate the IRB approval of this survey, the following language is required:

Hi all,

Recently, the MONSTER research group at the University of Florida has been developing DRAGON, a MATLAB based software tool for extracting quantitative information and reconstructing ODFs from texture data published as pole figures. It’s a bit niche, like any other specialized research tool, but we’ve seen a lot of interest in this kind of capability, so we are happy to announce that DRAGON is ready for beta testing! Because of the complexities of how pole figures are published, DRAGON relies heavily on user intuition and choices across a variety of parameters in order to extract quantitative information from images. We are undertaking a study to quantify the uncertainty inherent in the user input and how that uncertainty manifests in the reconstructed data.

We are looking for volunteers (age 18 and up) to participate in this study. The study involves using the current build of DRAGON to digitize several pole figures from synthetically generated ODFs, then answering a few questions about how the data input process. The study is anonymized and on a volunteer basis, with no obligation to participate. We also welcome any feedback about the DRAGON user experience.

The study instructions and data upload questionnaire are available at:


The study-ready build of DRAGON is available on GitHub at:


Our goal is to provide a useful research tool for the MSE community, and we thank you for your contribution to that effort!

This study has been reviewed by the Institutional Review Board, IRB202200720.