For the categories "data availability" and "analysis check" the colour code is a direct result of the evaluation results, as the outcome of the evaluation is a clear true or false indication. For the category "data evaluation", a small tolerance is included for simulation-based plausibility evaluation. This should reflect that simulations may contain several weaknesses (e.g. imprecise prediction of chemical shifts in NMR spectroscopy) and do not cover all aspects of necessary information (missing confidence for functional group prediction in IR simulation). The contributing aspects for a decision on the colour-coded review are available via a summary of the most important facts on which the result is based. The details also include information on the differences between expected and obtained results and, for transparency reasons, the corrections that were made by humans to revise the weaknesses of the simulation models if there are any (Figure ). For a review of data at a glance, the evaluation results -including all aspects of each analysis method -are reflected in one number ranging from -4 points (missing and probably false or contradictory information) to 10 points (data files, metadata, and analysis in full accordance with the expected outcome). This number should give a clear indication of the coherence of a dataset to be used for reviewing purposes but should also serve as a general indicator for comparing the quality of different datasets. To obtain a meaningful indicator, the results from the data tests are weighted, i.e. depending on the significance, informative value of the individual measurement method, and the accuracy of fit or susceptibility to the error of the respective test method, the individual evaluations from levels 1 and 2 are included to a different extent in the final evaluation.