To understand my perspective, it might help to think about the economic concept of opportunity cost. Why spend precious developer hours on building custom systems to do things that could be done cheaply and well with existing tools?
It took me about one afternoon to prepare this dataset using rsync, a text editor, a little bash scripting, and GitHub. I didn't know up front what interval I should use for the time lapse and sensor logging, so I logged more than I needed. I had to manually thin the images, but, in doing that, I learned what interval I want to use (1 hour). Now, I'll put that interval in my code, and my next data export will be even easier.
The benefit of approaching things this way is that I get to iterate fast and learn quickly. Using simple, flexible tools lets me spend a high percentage of my time on the interesting stuff--observing plants and learning golang.
[edit: Assuming that your data is stored under the hood in CouchDB, providing CSV/TSV export like you mentioned would be great. I'd encourage you to think about rsync too because it works really well for moving lots of images. I was regularly syncing over 2GB of ~1MB jpegs easily--that would be a huge pain in a browser.]