[wdmmg-discuss] CRA 2010: progress report [was: CRA 2010: description and questions]
William Waites
william.waites at okfn.org
Wed Aug 18 23:30:11 UTC 2010
On 10-08-18 23:57, Anna Powell-Smith wrote:
>> (disclaimer: I haven't looked yet at the 2010 data
>> but am assuming it isn't that different from the
>> 2009 data as I gather from the discussion so far)
> It is a bit different - there are two tables this year. One classifies
> items by COFOG2 but not regions (only by nation); the other has
> regions but not COFOG2. See Tables 9 and 10 at:
> http://www.hm-treasury.gov.uk/pesa2010_section4.htm
>
> Crucially, this means we have some COFOG2 information for local
> authority items, unlike CRA2009. Sorry, I should probably have
> highlighted that.
Ok. But we do seem to have the HMT Functional specification for
all of them. This seems very similar to the COFOG 2. Could we
use that? It would mean a new mapper, as you were
saying in IRC.
> We don't have to lose COFOG1, but I think we do have to lose the
> COFOG2 codes in Table 9, because it's either that or the regional
> information.
This is the part I don't understand. Why do we have to
make a choice between this and the regions? Can't we keep
all of it? If we guess the COFOG 2 from the FS then we have
everything we need. For the purposes of generating the
CSV version of the data, I would suggest just leaving the
"subfunction" column blank where the data comes only
from table 9 and let the loading machinery fix it. In my
opinion the CSV should be a straight transcription of the
XLS as far as possible.
There are also two columns I notice are being dropped
in the CSV reader - "ID or non-ID" (what does this mean?)
and the central/local government or public corporation
column... That might be useful otherwise for classifying
entities and government departments. See other thread
about the lack of good information on this.
Cheers,
-w
--
William Waites <william.waites at okfn.org>
Mob: +44 789 798 9965 Open Knowledge Foundation
Fax: +44 131 464 4948 Edinburgh, UK
RDF Indexing, Clustering and Inferencing in Python
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