Don't get me started on Euler angles.
Caveat being I'm more used to electron microscopy, maybe these things aren't as important with light microscopy because the resolutions are lower?
It's one thing for a highly-skilled user with a decade of experience to be able to import it eventually, another for an unskilled user to just have off-the-shelf tooling do it the same way for everyone automatically. This is more about meta-studies and unlocking new use cases. It sucks that the state-of-the-art for sharing academic microscopy data right now is basically looking at raster images embedded in PDFs, or email the authors, and then write a custom Scikit-Image script. Imagine if you had to read a PDF catalog and then email someone to order something off Amazon, or if your favorite CRUD app consisted instead of having an expert read a PDF and email a screenshots to you. What if sending those very emails to different recipients required implementing each users custom IMAP-like mail client. That sounds absurd, but it's kind of the way academic data sharing works now, lots of people are re-inventing the wheel and creating custom file formats.
Consider, for example, the work of Dr. Bik (example at [1]) who identifies cloned sections from microscopy data. Or what if, instead of each researcher having to generate their own images, or get lucky and remember a particular image there was a Getty Images/AP Newsroom platform where you could just filter for your particular subject and imaging parameters and share your data. A collection of proprietary RAW files with randomly-formatted Excel documents for metadata would allow individual researchers to get their work done, but would be pretty worthless in comparison.
[1] https://scienceintegritydigest.com/2023/06/27/concerns-about...
We support DICOM supp 145 too, but it's no panacea. There are still vendor specific quirks. The "surface" is larger (cause you expect all the metadata to be there in the standard format) so you still sometimes see differences.