Just a few days ago, on March 23rd 2022, we had the pleasure of hosting a workshop for “Reproducible Remote Sensing: Challenges and Evolution Possibilities”. It was so exciting to get together again, even in a hybrid format, to discuss such an interesting and interdisciplinary topic! As long as the o2r project has been running, we have approached the matter of reproducibility of scientific results from several perspectives, and now it was the time to frame the complexities of reproducibility in Remote Sensing. With this workshop, we wanted to explore the current and future possibilities of publishing reproducible research in Remote Sensing as a subdomain of Geoinformatics and for this purpose, a group of 17 people involved in different positions of the Academia was assembled, with everyone contributing their point of view to the discussion.
The workshop consisted of 2 breakout sessions. In the first part, we talked about our thoughts, the obstacles we encounter and the wishes we have regarding scientific knowledge in Remote Sensing that works reproducibly. In the second part, the discussion was mainly focused on the idea of creating an independent Journal for publishing Reproducible Remote Sensing papers, as a means of establishing reproducibility in this scientific field. The participants shared their experiences with regards to the state of reproducibility in their own work, they commented about the usability of o2r developed platform (https://o2r.uni-muenster.de) and outlined the positive aspects and the potential pitfalls of launching a fully reproducible Journal on Remote Sensing. After every session, the breakout groups presented their discussed points to the rest.
There were many interesting points raised throughout the whole workshop. The data appeared to be a tricky issue, as the sensitivity, the licensing and the size are parameters that very frequently do not allow for an end-to-end reproducible pipeline. The o2r system was characterized as a nice solution for early career scientists, because of its simplicity, and as an interesting learning tool. In the o2r team, we felt that reproducibility in Remote Sensing is so engaging to a big part of the community, that we could be deliberating for quite some time! We deeply thank all the participants and we are looking forward to future collaborations!