1st FAIL2FAIR Workshop in Bergün, Switzerland
Workshop aims
As part of the FAIL2FAIR project we organize two workshops. First, this one, aims to get input from the research community: software developers, facility staff and structural biology researchers, while the second workshop is dedicated to presentation and discussing results of this project.
The main question of the project, and this workshop, is how to make failed X-ray crystallography experiments better findable and reusable. We would like to discuss the following topics:
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Reference datasets for pathological cases
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Common pathologies in the images (e.g. ice, radiation damage, multiple lattices)
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Sample properties and solvent
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Metadata necessary for deposition and formats of thereof
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Automatic procedures analyzing images
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Compression (lossy/lossless)
Workshop is by invitation only. There is no fee for participating in the workshop, costs for stay and meals are covered by the project funding.
Organizers
- Paul Scherrer Institute (Filip Leonarski; local organizer)
- Molecular Biology Institute of Barcelona CSIC (Isabel Uson)
- University of Konstanz (Kay Diederichs)
FAIL2FAIR project
Macromolecular crystallography (MX) is a fundamental technique in structural biology. Its goal is the solution of the atomic structure of one or several macromolecules, and understanding of their function and physiological role. However, as currently established, this is an all-or-nothing procedure; therefore, data from unsolved cases, low-quality diffracting crystals, or problematic experiments are typically abandoned or discarded, limiting the potential for information extraction and methods improvement.
The Fail2Fair project aims to learn from failure. To this end, we will develop a pipeline to annotate and classify discarded crystallographic datasets and integrate them into the SciCat metadata catalogue, an Open Research Data infrastructure established at the PSI (Paul Scherrer Institute). By enriching SciCat metadata with detailed descriptions of crystallographic failure modes, Fail2Fair will make these datasets findable, accessible, interoperable and reusable to the scientific community in alignment with the FAIR principles and will support the advancement in the development of new tools, including those based on Artificial Intelligence (AI).
More details on project page.
Funding
FAIL2FAIR workshop is fully funded through the OSCARS project. The OSCARS project has received funding from the European Commission’s Horizon Europe Research and Innovation programme under grant agreement No. 101129751
