What logic to apply to evaluate update status in different datasets of the same dimension?


Hello all!

I’m uncertain about what to answer when you have datasets with different update status inside the same dimension.
For example, for National Statistics in Rio de Janeiro, Unemployment and Population is up-to-date, but GDP is outdated. I can explain that in the comments, but should I answer Yes (2 in 3 datasets are updated) or No (at least one of them is outdated)?

Thanks in advance @tlacoyodefrijol @Mor



Hi @Wagner_Faria_de_Oliv,

we defined the update frequency that it applies to all data. This means that GODI only “rewards” datasets whose elements are all up-to-date. In your case this would mean that you should answer “No” because one of data is outdated. But please do document that unemployment and population data are up-to-date. We will use this information to analyze how much deviation we have within each data category (e.g. how often are unemployment and population statistics provided timely, how often is GDP not provided) as part of our future refinement of timeliness.



That’s perfect, Danny. Thanks for your answer :slight_smile: