![]() I hope that the AFM field can work together to develop shared software that advances the field, and that all can contribute to and think GitHub is a brilliant way to do this, for example at As is evident, GitHub has great potential for sharing code, saving time, and fostering the AFM community. This accelerates research and delivers more value to funders. Sharing research software via GitHub or equivalents e.g., Gitlab, package repositories such as PyPI and sites like Zenodo or Figshare enables researchers to build on and reproduce each other's work. Overall increased sharing of code will help advance the AFM field faster and better, by reducing the barrier to more complex analysis and enabling us to build upon each other’s work all whilst increasing links between the community.Īlice: Software is increasingly being seen as a first-class research output equivalent to papers and datasets. Researchers that may not have the time or experience to write a completely new code could use and possibly adapt shared code to solve their own problems, gain completely new insight or automate lengthy analysis.Īutomated image processing and analysis is becoming increasingly important as we move to higher data acquisition rates through High-Speed imaging so sharing code will be important in this aspect. George: Although a lot of code is written to analyse very specific AFM problems, there is often significant overlap between other people's work who may be trying to perform similar analysis who would benefit from access to that code. I think especially as more and more AFM work involves machine learning and more complex analyses, reproducing the results will be very important. Raj: I don't know if GitHub specifically is important so much as just sharing code is important, so others can replicate the work. Why do you think others should use GitHub for AFM research? We hope that we will save all researchers in the field a lot of time currently spent processing their images and that TopoStats will help us move towards a place where no one presents images with image processing artefacts! This has been made possible using “GitHub Actions” and will result in a fast robust tool for the wider community. This is happening as the result of a KE grant from the University of Sheffield and has allowed us to bring in Research Software Engineers to work closely with our team. We are currently undergoing a major refactoring of TopoStats including adding automated testing and documentation to make this software easier for the community to use and contribute to. Personally, I often find errors or bugs in my own code when trying to use it in a new way so being able to update codes easily is great.Īdditionally, code doesn’t need to be linked to a specific paper, users can share anything that others might find useful on GitHub. As a user of other people’s code (not just for AFM analysis) I have already benefited and saved huge amounts of time from download code from GitHub.Īlice: By hosting our software on GitHub we have been able to share our software with researchers from the UK and beyond, enabling those researchers to contribute to the code, find bugs and suggest or implement features they’d like to use in their own image processing pipelines. Whilst code can be added to supplementary information, GitHub has the advantage that the code can be updated as needed. George: I find it a simple way to link potential users to code used in publications. For example, there's another package I sometimes contribute to but is mostly run by Oak Ridge National Lab called Pycroscopy ( ) that helps handle the data-processing side of microscopy. ![]() It's great to see what others do so you can think outside the box as well. Raj: I personally think science is a lot easier when you don't have to reinvent the wheel. What benefits did you find from using GitHub to share your AFM code/software? ![]() TopoStats carries out essential data handling, processing, and cleaning steps, which enables AFM to feed into downstream software designed for other formats of image data. Īlice: Our Software TopoStats is part of a larger movement to promote shared analytical infrastructure in AFM ( TopoStats is a foundational tool for AFM, written in Python, with the aim of enabling all AFM researchers to automate their image processing and obtain quantitative data from their images, without the need for user input. George: At the moment I have a few MATLAB codes to analyse HS-AFM Line scanning data, analyse fibrils/polymers in AFM images and a simple particle analysis code. I’m hoping to share many more tools in the near future. To be honest, I have to do a lot of work to make this more user-friendly since it probably won't work in other labs as is! But hopefully it gives others an idea of what you can do to manipulate the AFM. ![]()
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