Looking through Rufus slides from GIFT, I just wanted to share one thought I had while looking at fiscal data recently that may be relevant to it’s standardisation. It basically comes down to this:
Any piece of information that is used as metadata to describe a fiscal dataset in one context, will be part of the line-item data in another fiscal dataset. Hence, when standardising fiscal data, we should not distinguish data and metdata.
This probably deserves some explanation. An dataset may be labeled as “Budget of Country X” has the implicit metadata that it relates to country X. But in another dataset, perhaps for an INGO, “country” will be a column in the data and vary on a per-line basis. The same is true of datasets with names like “Health care spend in X”, “Revenues of the Government of X”: both also appear as in-data distinctions in other datasets.
This makes me think that trying to distinguish between data and metadata in these cases is not useful. It would be much more consistent to map fiscal datasets towards a line-based common mapping which allows for static field values, effectively stating: “All the line items in dataset X are about country Y”. Basically, all metadata fields in the data package would be modelled as dimensions with constant values.
What do people think?