Human- and computer-accessible 2D correlation data for a more reliable structure determination of organic compounds. Future roles of researchers, software developers, spectrometer managers, journal editors, reviewers, publisher and database managers toward artificial-intelligence analysis of NMR spectra.

The introduction of a universal data format to report the correlation data of 2D NMR spectra such as COSY, HSQC and HMBC spectra will have a large impact on the reliability of structure determination of small organic molecules. These lists of assigned cross peaks will bridge signals found in NMR 1D and 2D spectra and the assigned chemical structure. The record could be very compact, human and computer readable so that it can be included in the supplementary material of publications and easily transferred into databases of scientific literature and chemical compounds. The records will allow authors, reviewers and future users to test the consistency and, in favorable situations, the uniqueness of the assignment of the correlation data to the associated chemical structures. Ideally, the data format of the correlation data should include direct links to the NMR spectra to make it possible to validate their reliability and allow direct comparison of spectra. In order to take the full benefits of their potential, the correlation data and the NMR spectra should therefore follow any manuscript in the review process and be stored in open-access database after publication. Keeping all NMR spectra, correlation data and assigned structures together at all time will allow the future development of validation tools increasing the reliability of past and future NMR data. This will facilitate the development of artificial intelligence analysis of NMR spectra by providing a source of data than can be used efficiently because they have been validated or can be validated by future users.