So far as tables go,  I would look at the data model behind XBRL.

XBRL is sometimes maligned and often misunderstood,  but essentially it is a format for presenting multi-dimensional tabular information.  It is not really specific to finance,  but financial reports really are hypercubes so it fits that domain.

A wikified model would take more work,  but it may be the way to go.

One beef I have with time series data from the world bank is that many of them are piece-wise linear interpolated but don't document this.  A geometric interpolation would be more plausible for one thing,  but you see no bend in the curve caused by the '67 war in Nigeria,  and no evidence that experts think the the eye-popping population numbers for Nigeria are a bit high.

All of this matters little if you are doing a demo,  but if you really care what the population of Nigeria is,  this is a problem.


On Thu, Aug 6, 2015 at 9:58 AM, Daniel Kinzler <daniel.kinzler@wikimedia.de> wrote:
Am 06.08.2015 um 15:39 schrieb James Heald:
> Too much to input as individual statements on a single item each with a
> historical date qualifier, I would agree.
>
> But there really ought to be a good way to store serial or tabular data on-wiki,
> with wiki-style version tracking, that could then eg be specified as source data
> for the new graph extension, or for inclusion into columns or tables, or
> accessible at the level of individual cells for incorporation into infoboxes.
>
> Are there steps that people have taken in the direction of wikiesque storage of
> such serial or tabular data ?
>
> (Sorry if this is a perennial question, but it's something I've been wondering
> for a while now -- all the better if there is a standard FAQ response that
> somebody could direct me to).

We are thinking abotu it, but there are no concrete plans. We are really quite
busy as it is already...


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Daniel Kinzler
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Wikimedia Deutschland
Gesellschaft zur Förderung Freien Wissens e.V.

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Paul Houle

Applying Schemas for Natural Language Processing, Distributed Systems, Classification and Text Mining and Data Lakes