So Where Do the Numbers in Government Reports Come From?

Last week, the COI (Central Office of Information) released a report on the “websites run by ministerial and non-ministerial government departments”, detailing visitor numbers, costs, satisfaction levels and so on, in accordance with COI standards on guidance on website reporting (Reporting on progress: Central Government websites 2009-10).

As well as the print/PDF summary report (Reporting on progress: Central Government websites 2009-10 (Summary) [PDF, 33 pages, 942KB]) , a dataset was also released as a CSV document (Reporting on progress: Central Government websites 2009-10 (Data) [CSV, 66KB]).

The summary report is full of summary tables on particular topics, for example:

TABLE 1: REPORTED TOTAL COSTS OF DEPARTMENT-RUN WEBSITES

TABLE 2: REPORTED WEBSITE COSTS BY AREA OF SPENDING

TABLE 3: USAGE OF DEPARTMENT-RUN WEBSITES

Whilst I firmly believe it is a Good Thing that the COI published the data alongside the report, there is a still a disconnect between the two. The report is publishing fragments of the released dataset as information in the form of tables relating to particular reporting categories – reported website costs, or usage, for example – but there is no direct link back to the CSV data table.

Looking at the CSV data, we see a range of columns relating to costs, such as:

and:

There are also columns headed SEO/SIO, and HEO, for example, that may or may not relate to costs? (To see all the headings, see the CSV doc on Google spreadsheets).

But how does the released data relate to the summary reported data? It seems to me that there is a huge “hence” between the released CSV data and the summary report. Relating the two appears to be left as an exercise for the reader (or maybe for the data journalist looking to hold the report writers to account?).

The recently published New Public Sector Transparency Board and Public Data Transparency Principles, albeit in draft form, has little to say on this matter either. The principles appear to be focussed on the way in which the data is released, in a context free way, (where by “context” I mean any of the uses to which government may be putting the data).

For data to be useful as an exercise in transparency, it seems to me that when government releases reports, or when government, NGOs, lobbiests or the media make claims using summary figures based on, or derived from, government data, the transparency arises from an audit trail that allows us to see where those numbers came from.

So for example, around the COI website report, the Guardian reported that “[t]he report showed uktradeinvest.gov.uk cost £11.78 per visit, while businesslink.gov.uk cost £2.15.” (Up to 75% of government websites face closure). But how was that number arrived at?

The publication of data means that report writers should be able to link to views over original government data sets that show their working. The publication of data allows summary claims to be justified, and contributes to transparency by allowing others to see the means by which those claims were arrived at and the assumptions that went in to making the summary claim in the first place. (By summary claim, I mean things like “non-staff costs were X”, or the “cost per visit was Y”.)

[Just an aside on summary claims made by, or “discovered” by, the media. Transparency in terms of being able to justify the calculation from raw data is important because people often use the fact that a number was reported in the media as evidence that the number is in some sense meaningful and legitimately derived. (“According to the Guardian/Times/Telegraph/FT, etc etc etc”. To a certain extent, data journalists need to behave like academic researchers in being able to justify their claims to others.]

In Using CSV Docs As a Database, I show how by putting the CSV data into a Google spreadsheet, we can generate several different views over the data using the using the Google Query language. For example, here’s a summary of the satisfaction levels, and here’s one over some of the costs:

select A,B,EL,EN,EP,ER,ET

[For more background to using Google spreadsheets as a database, see: Using Google Spreadsheets as a Database with the Google Visualisation API Query Language (via an API) and Using Google Spreadsheets Like a Database – The QUERY Formula (within Google spreadsheets itself)]

We can even have a go at summing the costs:

select A,B,EL+EN+EP+ER+ET

In short, it seems to me that releasing the data as data is a good start, but the promise for transparency lays in being able to share queries over data sets that make clear the origins of data-derived information that we are provided with, such as the total non-staff costs of website development, or the average cost per visit to the blah, blah website.

So what would I like to see? Well, for each of the tables in the COI website report, a link to a query over the co-released CSV dataset that generates the summary table “live” from the original dataset would be a start… ;-)

PS In the meantime, to the extent that journalists and the media hold government to account, is there maybe a need for data journalysts (journalist+analyst portmanteau) to recreate the queries used to generate summary tables in government reports to find out exactly how they were derived from released data sets? Finding queries over the COI dataset that generate the tables published in the summary report is left as an exercise for the reader… ;-) If you manage to generate queries, in a bookmarkable form (e.g. using the COI website data explorer (see also this for more hints), please feel free to share the links in the comments below :-)