Abstract
The Editor-in-Chief introduces a new letter paper that includes open source optical network data.
© 2023 Optica Publishing Group
In this edition of the journal, we have our second letter paper [1]. This is intended to be a much shorter paper, but which we expect to attract a great deal of community interest. We encourage anyone who has something significant to say, to get in touch about contributing to this aspect of the journal. This particular letter describes some measured data from an optical network and makes this data freely available for all to explore.
We hope that this, and potentially other provisions of real network data, will be useful to the industry, as we develop intelligent algorithms to better manage and troubleshoot networks in the future. A popular current trend is the application of reinforcement learning to large optical network datasets, and this letter provides a highly useful input for anyone researching this area.
I hope you find this letter contribution interesting as well as the other papers in this issue of JOCN, which include the first set of papers in the collection from OFC 2023. Look for the remaining papers to be published in the February issue.
Editor-in-Chief
jocn@optica.org
REFERENCE
1. Z. Zhai, L. Dou, Y. He, et al., “Open-source data for QoT estimation in optical networks from Alibaba,” J. Opt. Commun. Netw.16, 1–3 (2024). [CrossRef]